English language Visionary Marketing Podcasts

The ebook self-publishing landscape has undergone a remarkable transformation over the past decade. What was once viewed with scepticism by the publishing industry has become a legitimate and often preferred path for authors worldwide. To understand the current state of this evolving market, we spoke with Kris Austin, whose platform Draft2Digital serves over 300,000 authors publishing more than a million titles across global markets. From Oklahoma City, he shared his insights on how independent authors are reshaping the publishing world. Inside the Ebook Self-Publishing Industry With market shares amounting to 40% of sales in the US, ebooks present new opportunities for writers who are able to benefit from self-publishing platforms like Self2digital. Can you introduce Draft2Digital and its mission? Draft2Digital currently serves over 300,000 authors who are independently publishing more than a million titles. We have been operating since 2012, and the industry has changed considerably during that period. Our goal is to help authors achieve their dreams by removing technical barriers and making the publishing process as streamlined and straightforward as possible. What languages and markets do you cover? We have published books in over a hundred languages. While English remains predominant, approximately 15 to 20 percent of sales come from non-English titles, with Spanish and German ranking as the second and third most popular languages. Our distribution reaches 180 countries, and about 40 percent of all sales occur outside the United States. ebook self publishing industry entrepreneur Kris Austin talked to us from Oklahoma City, OK. How has self-publishing evolved since 2012? When we started in 2012, self-publishing was still in its early stages. The real catalyst came in 2007 when Amazon released the Kindle, which sparked the explosion of digital books. Back then, there was significant stigma attached to being an independent author; many felt they were not as credible as traditionally published writers. Today, that perception has completely shifted. Many authors now choose self-publishing as their first option. We also see numerous hybrid authors who move between traditional and independent publishing, depending on their goals. The focus has shifted to the quality of the book and reader demand rather than the publishing model itself. What types of books dominate the ebook market? The majority of our ebooks are genre fiction: romance, fantasy, mysteries, and thrillers. These narrative fiction categories account for approximately 80 percent of ebook sales. Our print-on-demand service shows a different pattern, with roughly 40 percent fiction and 60 percent non-fiction. All these books are intended for consumer readers purchasing for personal enjoyment. Genre fiction (romance, fantasy, mysteries, and thrillers) amounts to approximately 80 percent of ebook sales Wit ebook self-publishing, authors can find readers anywhere in the world without leaving their homes. Image created with Midjourney Is ebook self-publishing viable for image-heavy books like photography? It is possible, though more demanding. Image-heavy books typically require a professional formatter to achieve the desired layout, particularly in digital formats where presentation can be challenging. For print editions, colour printing and layout involve additional complexity compared to text-only publications. What determines success in ebook self-publishing? The most successful authors treat publishing as a business. After creating a book they are proud of, they focus on marketing, discoverability, sales, and distribution. They approach it with an entrepreneurial mindset. However, it can also work as a part-time endeavour, particularly for authors writing series with multiple titles. One advantage of independent publishing is that you do not need a massive readership to succeed. Indie authors typically retain 60 to 80 percent of their sales revenue, allowing them to price competitively and target niche markets effectively. Even with just 2,000 potential readers, if you capture that audience and build loyalty, you can build a sustainable career. Indie authors typically retain 60 to 80 percent of their sales revenue If writing is your dream, ebook self-publishing could make it real draft2digital claims. How does Draft2Digital help authors reach global audiences? First, availability is essential. Authors upload their manuscript in Word format to our website, along with a cover image. I recommend not spending more than 100 dollars on a cover when starting out. Our system converts everything to digital formats and distributes to thousands of stores, including major online retailers, smaller platforms, and libraries across the US, UK, and Australia, typically within a few days. Accurate metadata, including title, description, and category, is crucial for helping readers find your book. What marketing strategies work for unknown authors? Discoverability is always a challenge. Successful authors connect with readers through social media, choosing platforms based on their target audience. Facebook may suit an older demographic, while TikTok reaches younger readers. Authors must identify where their audience congregates and invest effort in building those connections. Nothing comes free when selling a product; it requires consistent work. What are the main differences in reading habits across countries? Reading preferences vary significantly by region. Some countries, like the US, have high ebook adoption, while others, such as Germany, still favour print by a considerable margin. Certain markets, like Canada, show preferences for book bundles. Interestingly, German readers consume many English-language books, so we sell substantial quantities of English print titles there. What is the current balance between ebooks and print? When ebooks began growing around 2007, there were widespread concerns about the death of print. That never materialised. Ebook growth peaked around 2013, but print remained dominant. Currently, approximately 60 percent of books sold are print and 40 percent are ebooks, though this varies by genre. Romance readers predominantly purchase ebooks due to lower cost and convenience, while non-fiction readers prefer print for its tactile qualities and ease of reference. This ratio has remained relatively stable for years. Approximately 60 percent of books sold are print and 40 percent are ebooks Are people reading less than before? Readership fluctuates in cycles. We saw a significant peak during the COVID lockdowns, and we have been coming down from that high. However, engagement appears to be recovering. Books now compete with digital streaming and social media for attention, but dedicated readers will always find their books. We are optimistic that younger generations will discover books that resonate with them and develop reading habits. How is artificial intelligence affecting the ebook market? AI-written books exist throughout the market. We support AI as a tool for outlining, brainstorming, and various other assistance, much like word processors and spell checkers became standard aids. What we do not support is fully AI-generated content. AI-written books have become a significant challenge This has become a significant challenge, with platforms like Amazon being flooded with such material. It harms the industry and makes it harder for readers to find quality books. While AI may eventually produce excellent literature, we are not there yet, and this remains an ongoing challenge for the market. How do you help authors stand out in a crowded marketplace? We maintain merchandising relationships with all major retailers. Our mission is to identify promising books and propose them for spotlight placement and promotional features. We submit thousands of titles annually and achieve a 60 percent success rate. Authors can apply through our website to participate in these programmes. We also invest heavily in author education through our Self Publishing Insiders podcast, where we interview industry leaders, successful indie authors, and service providers to help authors improve their marketing and sales strategies. What do you predict for the future of digital publishing? Independent authors have proven their agility and ability to respond quickly to reader demands in an industry historically slow to adapt. Traditional publishers are increasingly looking to indie authors for insights on how to operate differently. They are actively recruiting successful independent authors into the traditional world. I expect traditional publishing to adopt more characteristics of indie publishing: greater agility, flexibility, and responsiveness. This convergence will continue accelerating over the coming years. Final thoughts about ebook self-publishing The ebook self-publishing revolution has fundamentally altered the publishing landscape. What Kris Austin describes is not merely a shift in distribution channels but a democratisation of authorship itself. With platforms like Draft2Digital removing technical barriers and providing global reach, the determining factors for success have shifted from gatekeepers to readers. For aspiring authors, the message is clear: quality content, business acumen, and direct reader engagement now matter more than ever. The stigma of self-publishing has given way to recognition that, ultimately, a book’s value lies in its ability to find and satisfy its intended audience, regardless of how it reaches them. Learn more at Draft2Digital The post Inside the Ebook Self-Publishing Industry appeared first on Marketing and Innovation.

Whereas artificial intelligence is reinventing Web writing, the written word has never been more valuable. Selim Niederhoffer, a copywriting trainer and bestselling author, has recently been exploring how marketing professionals can still succeed amidst “enshitification“, online influence, and automation. Meet an expert who remains confident in the power of words. Copywriting in the age of AI: why words retain all their magic Niederhoffer is adamant: despite GenAI, the written word retains its magic — image produced with Midjourney Human vs. AI Selim, a seasoned copywriter and author is keen on using what he calls “magic words.” Ask him why and his answer might surprise you in this age of sheer automation. “I’ve already been thinking about magic words for years. I want to dig deeper, show real examples and, most importantly, explain why they actually work.” Pen and paper His approach remains resolutely traditional. “I genuinely work with a pen and paper.” This approach reveals something fundamental about Web writing: it works when you truly understand the psychology behind it, not when you just mechanically apply copywriting techniques. Selim bases his work on well-established principles of persuasion. Selim Niederhoffer still believes in the virtues of word magic in Web writing — image produced with Midjourney “When there’s a principle of persuasion, there’s usually a word that goes with it. Take urgency or scarcity, for example. If something’s rare, that means limited places, running out of stock… that sort of thing. That’s how I build my word cluster. The research then extends to field observation. “I look at what my clients are using, what’s going on at Burger King, McDonald’s, Nike. I check out the major brands too – what they’re doing on YouTube, on LinkedIn.” Eventually, Selim identified 55 magic words but trimmed them down to 50. It’s an approach that perfectly shows what still sets humans apart from machines: the ability to critically analyse and curate with discrimination. However, it’s worth adding nuance. Selim can’t conceal that he genuinely “loves” ChatGPT. As we’ll see later, this raises some legitimate questions. Thank you! the ultimate magic word Among the 50 words he’s analysed, the first is also the simplest: thank you! For Selim, this should be essential for every business. “How many times have you walked out of a shop where the sales assistant just didn’t seem to have noticed you? Whether you bought anything, or didn’t doesn’t make any difference, once the transaction’s done, you’re out the door.” Yet some brands know how to thank their customers. “Nespresso or Apple, for example: the Nespresso employee comes out from behind her counter, she hands you your product. Thank you for your visit. Have a nice day! That’s how it should be.” For Selim, saying “thank you!” is more than just being polite, it’s a way of life. “You can go further: thank you for your visit, thank you for subscribing to the newsletter, thank you for your comment. You need to constantly think in terms of gratitude.” This approach fits into what Gary Vaynerchuk called The Thank You Economy. “We’re in an attention economy,” Selim explains. The stakes are high in Web writing: how do you maintain this human dimension at corporate scale? “For me, the essence of business is that there’s a person in front of you who’s exchanging something with you. That’s really the foundation. But today, how do you keep that at corporate scale?” Data confirms an intuition: gratitude improves customer experience and encourages loyalty. A valuable lesson for all those who practice Web writing and seek to create a lasting connection with their audiences. You need to seek to create a connection with your audiences — image produced with Midjourney AI and Web writing: threat or opportunity? The conversation inevitably turns to artificial intelligence. For Selim, AI is first and foremost an incredible productivity tool. “If I’ve got a newsletter to write, I’ll use AI. Sales pages? AI. The thing is, AI works brilliantly for me. I’ve even become clearer in my writing,” he admits without hesitation. But he’s not entirely starry-eyed about it. He’s identified three major pitfalls that professionals absolutely must avoid. The three pitfalls of AI in copywriting The first pitfall is wordiness. “ChatGPT tends to waffle because it’s been trained on Reddit, Wikipedia, and similar sources. However, in real life, when we write, we cut down to the core, deleting most of what we initially write.” The second limitation is related to syntax. “AI tools have their favourite phrases. It can be a bit clunky. It’s got that ‘ChatGPT-ish’ quality – you know it when you see it. After a while, you can spot AI-written text a mile off.” The third issue, and the most surreptitious one, is lack of personality. “When we just use basic LLMs, we lose our tone of voice, we lose what makes us different, we lose what makes people go ‘Ah! That’s Selim, that’s Yann’. That personal touch. I’d say that’s the biggest danger AI poses for copywriters, Web writers, anyone working in this field.” For him, the key questions are: how do you refine AI, how do you avoid its main pitfalls, how do you stay in control and how do you harness all its power? This evolution shows a profound shift in the profession: the copywriter is becoming an orchestrator of AI platforms. Losing our skills Selim warns against a hidden danger: declining skills. He reminds us that the brain is a muscle, and using it creates connections. However, if we stop using it, those connections are lost. He admits that he has fallen victim to this himself. “I have noticed that my writing isn’t as fluid as it used to be when I’m starting from scratch. Between 2010 and 2022, I was churning out three to five blog posts a week. Now, if I can just knock up a prompt, get a result and tweak it a bit, job done. But it’s less satisfying.” This awareness led him to experiment. “I run A/B tests. Send out version A written by AI, version B written by me, then see who clicks more. I check which headlines work best, which text performs better,” he explains. It’s a data-driven approach that could bruise his ego, he admits with a laugh, but it’s essential for understanding what genuine human value looks like in Web writing. What human added value tomorrow? The final question comes naturally: will humans still add value compared to machines in a year or two? Selim remains cautious about making predictions. “I’m rubbish at forecasting because I don’t spend enough time on it,” he admits candidly. But his reading of the market reassures him. While I can see companies increasingly launching AI training for their staff, there’s always the question of depth. Are they adequately trained and properly supported? Web writing needs remain massive “I meet marketing directors who want me on their pay-roll. We’ve got so much work to get through that we’d need ten people using ChatGPT just to keep up,” he reports. This suggests that AI isn’t so much replacing writers as it is multiplying opportunities for content production. Selim’s thoughts tap into bigger questions about how work is evolving. “The idea of heading towards a society where people become useless doesn’t surprise me. I’ve seen it enough times in sci-fi,” he confides. This vision actually mirrors history: villages like ours in the Pyrenees, with thousands of inhabitants at the turn of the 20th century now down to a few dozens. Economic and technological shifts have always redrawn the employment map. What the future holds for Web writing This conversation with Selim Niederhoffer sketches out the shape of Web writing as it transforms. Words remain magical, but how we summon that magic is changing. AI’s becoming a powerful content production tool, but the real value still lies in properly understanding how persuasion works, in being able to orchestrate these tools cleverly, and in keeping a human tone of voice. Here’s the paradox: just when machines can churn out infinite text, what becomes scarce is quality strategic thinking, subtle psychological understanding, and the ability to inject real personality into content. Selim’s magic words are just a a beginning – they are mere ways of understanding what makes human readers tick. A hybrid Web According to Selim, tomorrow’s Web writing will be hybrid – a collaboration between human and machine. It will demand technical mastery of AI tools, but it’ll be rooted in a deep understanding of how persuasion actually works. In short, words will always be magical, but that magic needs cultivating, training, constant work – otherwise it will erode in the face of automation’s easy appeal. One needs to keep reading, discussing and engaging with real people. That’s how we will train our brains and hang onto that human edge that makes all the difference in Web writing. 10 of Selim’s 50 magic words Here are 10 words taken from Selim Niederhoffer’s book “Les Mots Magiques” (Magic Words), which are effective words to boost your marketing content and encourage action: Please Thank you New Since Out of stock Free Now or never Satisfaction guaranteed or your money back Hundreds of people already trust us First name The post Web writing : words retain all their magic appeared first on Marketing and Innovation.

Commentary on the environmental impact of AI often swings wildly between doom-and-gloom catastrophism and blind techno-optimism. But where’s the truth in all this? On July 24, 2025—the symbolic date of Earth Overshoot Day—we sat down with Yves Grandmontagne, founder and editor-in-chief of DCMAG (Data Centre Magazine*), to get his take on AI and its real environmental impact. It is worthy of note that Yves and I explored Silicon Valley’s infrastructure innovators together through extensive press tours some time ago. This provided us with firsthand insight into the tech industry’s approach to these challenges. The current annotated transcript of our interview is a summary of our thorough, nuanced, and let’s admit it, quite lengthy discussion. You are therefore encouraged to treat this article as your starting point for diving deeper into this extremely complex topic. Exploring the Real Environmental Impact of AI What’s the real environmental impact of AI? An employee keeps watch over the cooling units at Orange’s data centre in Val de Rueil in Normandy, France — Photo antimuseum.com * DCMag is only available in French This post summarises what turned out to be an incredibly rich hour-long conversation. The sheer complexity of this topic forced us to dig into multiple technical, economic, and environmental angles—making any kind of comprehensive analysis near inconceivable. Drawing on his deep expertise in the data centre and AI sectors, Yves Grandmontagne gives us some much-needed factual perspective on a debate that’s often polarised between doomsday scenarios and over-the-top techno-optimism. To tackle this properly, we decided to take recent quotes—both positive and negative—and fact-check them with our expert. Yves’s analysis helps us cut through the noise and understand what’s really at stake in this technological breakthrough. Environmental Impact of AI: Reality Check Time TLDR: Environmental Impact of AI The electricity consumption issue is more nuanced than you think* – AI will represent 20-30% of data centre consumption (not twice that number), and only 2-4% of overall electricity consumption Energy efficiency gains are actually remarkable – Over the last decade: number of data centres x2, floor space x4, but energy consumption up only 6% Beware of dubious comparisons – Comparing a ChatGPT query to Google search is methodologically flawed (completely different technologies and services) Water consumption varies massively by geography – Huge issue in the US, but Europe has been using smarter closed-loop systems for ages Tech innovations look promising – New technologies (direct liquid cooling, immersion cooling) are slashing water and energy consumption AI might actually be part of the solution – Can optimise energy mix management and electricity transport, which is currently our main bottleneck Let’s get some perspective here – Data centre impact remains pretty marginal compared to the chemical industry (32% of French energy consumption) or agriculture *All numbers by Yves Grandmontagne at Data Centre Magazine Bottom line: The impact is “real but massively overstated”—we need to put things in context and remain cool and collected. So here are the quotes about the environmental impact of AI that we wanted to fact-check with Yves. Rumours vs Reality: Decoding the Doomsday Predictions Predictions of Booming Electricity Consumption The first claim I put to Yves Grandmontagne was Synth Media’s prediction [Fr] that “AI’s growth could double data centre electricity consumption by 2026.” His response immediately throws cold water on this alarmist take: “It’s absolutely true that AI is rolling out infrastructure at breakneck speed and eating up more space in data centres. Sure, it’s going to significantly bump up their energy consumption—no question about that. But will consumption actually double? I seriously doubt it. AI should account for somewhere between 20 and 30% of global data centre consumption worldwide.” A data centre server rack — photo antimuseum.com AI should account for somewhere between 20 and 30% of global data centre consumption worldwide This reality check reveals something consistent throughout Yves Grandmontagne’s analysis: the absolute need to put numbers in context. The expert points out that this increase is just part of the natural progression tied to our ever-growing digital habits. “What’s driving this consumption increase is our daily usage, whether that’s for work or for personal reasons,” he reminds us, highlighting our collective responsibility in this evolution. It’s a topic we’ve tackled before with a broader focus on digital consumption. The most striking part of his analysis is about the energy efficiency angle. Contrary to popular belief, data centres aren’t following a consumption curve that mirrors data growth. This improving efficiency is something that gets completely overlooked in public debates about the environmental impact of AI. ChatGPT’s Carbon Footprint: More Context Needed When it comes to the 10,113 tonnes of CO2 equivalent attributed to ChatGPT usage in January 2023 (Basta Media – Data for Good, AI has the potential to destroy the planet), Yves Grandmontagne takes a refreshingly pragmatic approach: “I can’t verify that exact figure. Getting that precise—down to 10,113 tonnes—represents a massive methodological challenge, especially when you’re dealing with AI infrastructures that are distributed systems.” We asked Yves Grandmontagne, editor-in-chief of DCMAG (Data Centre Magazine) to give us the real story about the environmental impact of AI — He gave us facts and figures, which we’ve compiled in the infographic at the end of this post This observation raises a crucial methodological point: just how tough it is to accurately measure the carbon footprint of distributed infrastructures. The expert does acknowledge this pollution is real, but puts it in perspective: “Those 10,113 tonnes of CO2 still represent volumes significantly smaller than what many other industries pump out.” This contextualisation isn’t about downplaying the issue—it’s about keeping things proportional. Yves Grandmontagne reminds us of a basic truth that is often overlooked: “The moment we use our smartphones, we become CO2 producers.” This highlights the inconsistency in criticisms that single out AI from our overall digital consumption. The Google vs ChatGPT Comparison: A Methodological Trap Watch out for convenient shortcuts between pollution and digital tech—they’re everywhere and pretty handy when you want to hide overall industrial pollution — image created with Midjourney MIT’s claim that “a ChatGPT query uses ten times more electricity than a Google search [p 9]” perfectly illustrates the danger of oversimplified comparisons, according to Yves Grandmontagne. His take is particularly eye-opening: “This comparison just doesn’t work. I think we’re making a fundamental methodological error here because we’re comparing two completely different technologies. Google is a search engine that gives you results that you then have to sift through to find what you’re actually looking for. ChatGPT, on the other hand, serves up information that’s already structured and ready to use.” “The more we use computing, and the more we use AI, the more we consume.” User responsibility matters — images antimuseum.com Orange data centre in Val de Rueil This analysis shows just how sophisticated you need to be when evaluating the environmental impact of AI. A ChatGPT query might actually replace multiple Google searches plus visits to various websites. That makes direct comparison pretty meaningless. This distinction will probably become moot anyway with the rollout of Google AI Overviews, which will integrate similar functionality to ChatGPT. The Water Issue: Geography Matters More Than You Think New data centre cooling techniques work in closed loops. Image antimuseum.com Orange data centre in Val de Rueil Massive Geographical Differences One of the most revealing parts of our interview dealt with data centre water consumption. Yves Grandmontagne draws a crucial distinction between American and European practices: In the United States, when you install a data centre, you’re a private company reaching out to other private companies for water on one side, electricity on the other. And the utility companies that manage energy or water are thrilled to have a massive client that’ll absorb a chunk of their production. This geopolitical insight explains those 5.4 million litres of fresh water attributed to ChatGPT-3 training. The issue isn’t the technology itself—it’s local practices and regulations. In Europe, our expert reminds us, “we’ve been developing infrastructure cooling systems that work in closed circuits or are air-based rather than water-based for quite some time”. Take Orange’s data centre in Val de Rueil, for instance—it’s cooled by the crisp Normandy air. The only exceptions are during heat waves, which are naturally time-limited. How Cooling Actually Works Yves Grandmontagne’s technical explanation demystifies the cooling process: “Water acts as a conductor to capture heat.” He then breaks down the dual-circuit system that protects infrastructure while managing thermal exchanges. This approach reveals that warm water discharge from data centres (~20-25°C) stays well below that of nuclear plants (27-35°C for the Gravelines nuclear plant in the North of France). That gives us a useful comparison point for our debate. Warm water discharge from data centres (around 20-25 degrees) stays well below that of nuclear plants (27-35°C for Gravelines) We should note that these figures vary depending on location, time of year, and technological choices. A 12°C increase in the North Sea, even if reports show nothing concerning at the macro level, pro

Will the AI bubble burst or is GenAI here to stay? The artificial intelligence industry is experiencing unprecedented financial euphoria. Yet, the current situation is very confusing. AI investments are reaching dizzying heights. Let’s mention OpenAI’s $40 billion funding round at $300 billion valuation and Mistral AI’s €1.7 billion funding round. Yet, some commentators are very critical of the situation. For instance, Ed Zitron predicts that the AI bubble will burst in Q4 2025. All this is fueling intense, rather than rational, debate. I wanted to confront these concerns with the expertise of Bernhard Schaffrik, Principal Analyst at Forrester Research. His analysis is insightful and nuanced. In his mind, there will be some sort of correction, but at the same time, GenAI is too popular to disappear. When Will the AI Bubble Burst? Is the AI bubble about to burst or is GenAI here to stay? Forrester’s Schaffrik predicts corrections but says GenAI is too popular to go — photo by Forrester.com Forrester’s Bernhard Schaffrik is recognized as one of the most insightful experts in artificial intelligence. He provides a nuanced analysis that transcends simple financial considerations. His perspective on the AI bubble burst scenario offers first-hand insights for understanding where this transformative technology is truly heading. The AI Bubble: Financial Reality, Technological Continuity The question of a potential AI bubble burst cannot receive a univocal answer. As Bernhard Schaffrik rightfully points out, it all depends on one’s perspective. This duality of vision probably constitutes one of the keys to understanding the current situation and the likelihood of an AI bubble burst. Like us, Schaffrik righfully points out that the main issue with AI is societal and philosophical — image generated with Adobe Firefly “It’s almost impossible to get a one-sentence response from an analyst. Allow me two sentences. Number one is, of course, it always depends on the role or the profile you’re asking. If we are talking about financial investors, then yes, there are strong signals of this being a bubble because there is so much money being pumped into it—more than $120 billion US dollars in capital expenditure on AI infrastructure alone, just by the Magnificent Seven tech providers. So that bubble could burst,” explains Forrester’s expert. This assessment gains particular relevance when considering Google’s $9 billion AI data center investment in Oklahoma for advanced AI training infrastructure. This financial perspective, however, tells only part of the story. Technological adoption follows a different logic from financial markets, as Schaffrik confirmed during our exchange about the AI bubble burst potential. “But now, if you put yourself in the shoes of enterprise decision makers, tech decision makers, also AI users, there are many who would say, ‘I don’t care if that bubble bursts, the technology is there, and it won’t go away.’ “Regardless of the amounts all the financial transactions surrounding the AI industry, people are actually using this technology. And they like what they are seeing. It might not be the disruptive, transformative value some are surmising. It’s probably more incremental than that, but the adoption of that technology is undeniable.” The Revenue Challenge: A $25 Billion Gap to Bridge Fortune’s analysis reveals a concerning gap between current investments and generated revenues. To justify current investments, AI companies would need to generate $40 billion in annual revenue, while they currently produce only $15 to $20 billion. Schaffrik doesn’t believe in an AI bubble burst right now — image made with Adobe Firefly I was wondering whether this $20-25 billion gap could represent a systemic risk that could trigger an AI bubble burst. Schaffrik remains relatively optimistic on this point: “There is still enough money in that market to back these revenue gaps at least for a while. And what I’m also seeing is that especially when it comes to the largest enterpriseson the planet, they are convinced to continue using that software. And if it comes at a premium which is decent, arguably, maybe a couple percentage points higher than what they are paying today for the software, then this seems to be acceptable.” This acceptance of additional costs by large enterprises stems from the incremental value they perceive, even if it hasn’t yet reached the promised transformation level that might prevent an AI bubble burst scenario. LLM Regression: A Warning Signal? A particularly troubling element in the current ecosystem is the recent NewsGuard study revealing that major LLM systems are no longer progressing but regressing, generating more hallucinations and errors. This observation raises fundamental questions about current technology maturity and its impact on AI bubble burst predictions. “I’m not saying that LLMs and generative AI are progressing in a linear fashion nor that this technology will be disruptive in any way, despite the promise. As we have seen with emerging technologies for decades and even centuries, it takes breakthrough technological revolutions rather than evolutions to fulfill such promises,” analyzes Schaffrik. This vision of the current limitations of AI doesn’t diminish Bernhard’s long-term optimism: “But I’m also convinced that these breakthroughs will happen, not within the next seven, eight, nine, 12 months, but maybe in the long term. Something else will be coming up.” Energy Efficiency: The Achilles’ Heel of AI One of Schaffrik’s most compelling criticisms concerns the energy efficiency of current systems. His comparison between the human brain and data centers is striking and relevant to understanding whether we’re facing an AI bubble burst. “If we look at the amount of energy our brains are requiring to create a certain inference, and how much an LLM would require to achieve the same result with electricity, this cannot be the way forward.” This energy inefficiency constitutes a major barrier to scalability and will require significant technological breakthroughs to overcome, potentially influencing AI bubble burst timing. Pilot Failures: Business as Usual or Red Flag? The 95% failure rate of corporate AI pilots revealed by MIT research might seem alarming and suggestive of an impending AI bubble burst. Yet Schaffrik places this figure in its historical context: “It’s quite normal. As an analyst covering innovation management, what I have been observing over time is that about 10% of all innovation-related minimum viable products, proof of concepts, pilots, will turn into a product.” The problem would rather lie in unrealistic expectations: “Everybody rushed at it because one believed that since it’s accessible through natural language, it should  be easier to deploy, to implement, and there are no drawbacks and negatives. That might explain that the failure rate is slightly higher than with technologies we saw in the past.” This assessment aligns with Gartner’s prediction that 30% of GenAI projects will be abandoned after proof of concept by 2025 due to poor ROI and unclear business value. AGI: The Next Revolution in Motion Despite current limitations, Schaffrik maintains his bold prediction from his July 2025 analysis “Demystifying Artificial General Intelligence” that Artificial General Intelligence (AGI) represents “the biggest change in tech we have ever seen and is starting right now.” This vision, which could influence AI bubble burst scenarios, is structured around three maturity stages. “Competent artificial general intelligence is lurking around the corner. Our prediction is that between 2026 and 2030, we will see competent artificial general intelligence. You could think of it as your first trustworthy AI agent. You might not want to give it your car keys or your wallet, but it might do amazing things.” The subsequent stages would unfold over more distant horizons: independent AGI within the next five to ten years, And lastly, strategic AGI in a more distant future. Current AI Limitations: Experience versus Training A crucial point raised in our discussion concerns the difference between training and experience. As I pointed out to Schaffrik, experience develops critical thinking that current LLMs don’t yet possess, which could impact AI bubble burst predictions. “We might get to a point where most of us humans wouldn’t be able to tell if on the other side, a human or a machine is interacting with us. There will be areas where we will still be able to tell. But experience is something we could at least partially solve with more data and better data,” states Schaffrik. The solution, according to him, lies in massive data collection: “So much of the billions of investment money flowing now into all these big companies is also to collect and curate data also from the physical environment. Bringing all this data together, will create something that mimics experience.” The Human Factor: What’s Left for Us? The philosophical question of what humans will do when machines surpass us in thinking capabilities represents Schaffrik’s personal concern regarding potential societal implications of advanced AI, regardless of any AI bubble burst. “That’s my personal doomsday scenario, I must say. It’s not good for us humans to just idle around. So it’s not so much a technical conversation, but more a political, societal, psychological and philosophical one. So I’m sure we are far away from this, but we are getting there.” Leadership and Preparation: The Governance Challenge Regarding leadership in this transformation, Schaffrik acknowledges the complexity: “Rulers are supposed to rule. The question is more like, are they intentionally gathering a diverse set of experts who would be able to consult them? Technically, this is possible. Are they willing to? I

The world of artificial intelligence is evolving at breakneck speed, and nowhere is this more conspicuous than in the emergence of AI agents. As organizations grapple with separating genuine innovation from marketing hype, we sat down with Ed Keisling, Chief AI Officer at Progress Software, to cut through the noise and understand what AI agents really mean for businesses today. Ed brings a unique perspective, having taken on his new role in February 2025 at a time when the industry is proclaiming this as “the year of agents.” His insights reveal both the tremendous potential and the current limitations of this transformative technology. As always, time is of the essence. AI Agents, Beyond the Hype Preogress Software’s Ed Keisling did a great job debunking the myths surrounding AI Agents and showing what the future holds beyond the hype – photo Progress Software. The Rise of the Chief AI Officer: A Strategic Imperative The creation of Chief AI Officer roles across the technology industry signals more than just a trend—it represents a fundamental shift in how businesses view artificial intelligence. As Ed explains, “AI needs to be a strategic pillar of a business to drive innovation and growth. It really reflects the pace at which technology is evolving, and having somebody that is accountable to follow all these latest updates and really look at it through the lens of new risks and opportunities.” This observation resonates with the broader digital transformation patterns we’ve witnessed over the past decade. Just as Chief Digital Officers emerged to guide organizations through the digital transformation revolution, Chief AI Officers are now stepping up to navigate the AI transformation. The role isn’t merely about implementing technology—it’s about strategic thinking, risk assessment, and identifying genuine business opportunities in a rapidly changing landscape. AI agents: the promise with tools like Manus is that they would behave like your favourite dog. Go search, Rover…! — photo by antimuseum.com Defining AI Agents: Beyond the Buzzwords One of the most persistent challenges in the AI space is the confusion surrounding terminology. AI agents, in particular, have become an overloaded term that means different things to different people. Ed provides valuable clarity by positioning agents on a spectrum of AI capabilities. “When generative AI came out, it was generally reactive,” Ed notes. “We would go to ChatGPT, provide a prompt, and it would generate a response based on its training patterns. Agents are moving along that spectrum in terms of capabilities—they have the ability to perceive their environment, access to audio, video, documents, and crucially, the ability to reason, plan, and learn from their actions.” Unfortunately, Rover isn’t always willing to search in the right direction… — photo by antimuseum.com Traditional automation relies on strict rule-based systems—the digital equivalent of if-then-else logic. Chatbots, while more sophisticated, remain predominantly reactive. AI agents represent a step toward proactive, reasoning systems that can adapt to changing circumstances. AI agents represent a step toward proactive, reasoning systems that can adapt to changing circumstances The evolution doesn’t stop there. Ed introduces the concept of “agentic AI“—a broader paradigm where multiple agents collaborate, passing context between each other to accomplish complex tasks. This represents the holy grail of AI automation: systems that can dynamically adapt to real-time situations without constant human intervention. Reality Check: Why Perfect Automation Remains Elusive Despite the exciting potential, Ed provides a sobering reality check about current capabilities. His observation about the Pareto principle in AI is particularly insightful: “AI is the ultimate manifestation of the 80/20 rule. You can very rapidly get to value with 20% of the work achieving 80% of the results, but actually getting it to work 100% of the time is still very, very difficult.” This phenomenon explains why AI demonstrations look so compelling while real-world implementations often fall short of expectations. The gap between proof-of-concept and production-ready systems remains significant, requiring careful planning, clean data, and well-defined business processes. As always, I should add, “the more it changes, the more it stays the same,”as the French poet would have it. RAG Technology: Making AI Practical for Business While pure AI agents may still be evolving, Progress Software’s acquisition of Nuclia, an agentic RAG (Retrieval Augmented Generation) provider, demonstrates a more immediate and practical application of AI technology. Ed explains the fundamental problem RAG solves: “Large language models have been trained on the entirety of the Internet, giving them broad general knowledge, but they don’t have access to data stored behind firewalls or on personal computers.” This limitation is critical for businesses. While public AI models are impressive, their real value emerges when they can access and reason about proprietary business data. RAG technology bridges this gap, allowing organizations to leverage AI’s reasoning capabilities while grounding responses in their specific knowledge base. The practical implications are significant. As Ed points out, “Small to medium-sized businesses have lots of unstructured data—audio, video, log files, recordings, PDFs, charts—that represent proprietary business value, but they have no way of indexing or finding or correlating the data within it.” RAG technology makes this data accessible and actionable. It’s high time to stop AI-Washing Ed Keisling advises — image created with Midjourney Separating Innovation from AI Washing Ed’s experience at the AI4 conference provides valuable insights into the current state of the AI industry. His observation about AI washing is particularly relevant: “There was a lot of AI washing—companies that weren’t sure they understood the problem to be solved, with very thin wrappers around language models to solve point problems. It felt like a hammer looking for a nail.” The key differentiator, according to Ed, lies in problem-solving focus rather than technology-first thinking. “AI allows you to solve old problems in a new way and to make seemingly impossible problems possible. You’re thinking about how to drive outcomes—making developers more productive, automating tedious workflows, providing better insights that weren’t possible before.” This perspective aligns with successful technology adoption patterns throughout history. The most successful implementations focus on specific business outcomes rather than showcasing technological capabilities. Real-World Value: ShareFile’s Document Intelligence Progress Software’s ShareFile platform provides concrete examples of AI delivering measurable business value. The platform serves client-facing teams in regulated industries—doctor’s offices, law firms, and tax accountants—where document management is critical but time-consuming. The AI implementations are practical and measurable: “We can create curated lists of documents appropriate based on your situation, and as you upload documents, we can figure out which document relates to which checklist item. We’ve measured this at being three and a half times faster.” More importantly, the system addresses security concerns that many organizations face: “We have capabilities that scan for social security numbers, personal information, and credit card information that you didn’t want to upload. This single capability flags around 35,000 documents a week.” These examples demonstrate AI’s sweet spot: automating routine tasks while enhancing security and accuracy. The value isn’t just in speed—it’s in freeing professionals to focus on high-value work instead of admin tasks. The Human Factor: Reskilling Rather Than Replacing One of the most contentious aspects of AI adoption concerns workforce impact. Ed’s perspective is refreshingly pragmatic: “This is a fundamental reshaping of how business is done—a new skill and opportunity for people to grow, learn, and reinvent themselves. There aren’t experts who have been doing this for five or ten years. If you have the headspace and desire, you can become that expert.” This view positions AI as an enabler rather than a replacement. The technology’s real power lies in eliminating organizational silos and enabling individuals to accomplish more with the right tools and training. “One person is now going to be capable of doing multiple things with the right prompts, giving them opportunities to do more and drive more value for the organization.” The message is clear: organisations with infinite backlogs of valuable work don’t need to fear AI displacement. Instead, they should focus on upskilling their workforce to leverage these new capabilities effectively. Looking Forward: Practical Adoption Strategies Ed’s recommendations for AI adoption focus on practical, incremental approaches rather than transformative leaps. “There’s enormous green space for individuals to become fully enabled with AI. The majority of people using AI today are using it in a Google-like fashion, but they haven’t taken time to understand how to correctly prompt agents or use advanced capabilities.” The most successful implementations start with individual productivity tools—document summarization, email assistance, and internal search capabilities—before advancing to more complex agentic systems. This approach allows organizations to build AI literacy while demonstrating concrete value. In Conclusion, Embracing Reality While Preparing for the Future Our conversation with Ed Keisling reveals that AI agents represent both enormous potential and significant current limitations. While the vision of fully autonomous A

In an era of overtourism, where mass travel increasingly strains destinations worldwide, Christopher Hill offers a compelling alternative with his voluntourism/volunteer travel business, Hands-Up Holidays. As a founder and managing director of this company, Hill has built a business model that demonstrates how travel companies can be forces for good rather than exploitation. His approach to volunteer travel challenges the conventional wisdom that luxury and social responsibility cannot coexist. Voluntourism: When Volunteer Travel and Luxury Coexist For Mutual Benefit Voluntourism is a portmanteau expression combining “volunteer” and “tourism” — Photo from Hands Up blog post on Earth Day Eco-Luxury Inspiration (Mexico – conservation of turtles in Baja California by Christopher Hill) What makes Hands Up Holidays’ philosophy particularly noteworthy is its commitment to controlled growth, prioritising quality experiences over scale. Rather than pursuing rapid expansion that could compromise his mission, Christopher Hill maintains personal oversight of every client interaction, proving that sustainable business practices can create more meaningful outcomes for travellers and communities alike. Operating across over 30 countries, Hands Up Holidays represents a fascinating case study in how the apparent contradiction between luxury accommodations and volunteer work can enhance both experiences. Here is the account of our interview. What kind of work are your clients doing during their volunteer travel? We offer a great variety of projects. Our most popular initiatives are building projects, which can range from small-scale but highly tangible endeavours like constructing or installing eco-friendly stoves in village homes to larger undertakings such as helping build houses or renovating school classrooms. Beyond construction, we focus heavily on wildlife conservation projects, where families might care for elephants or participate in sea turtle protection programs. The third major area involves educational support, particularly serving as reading partners in local schools. Each project is carefully selected to ensure meaningful impact while being suitable for family participation. Nayara Tented Camp – The tented camp was built on stilts and a lot of space was left between tents to plant trees and palms between them. Thousands of trees and indigenous bushes have been planted to reforest and repair damage done by cattle farmers. Energy and water conservation measures are in place. The majority of the team is from the local town, and free transport and health services are provided. What triggered your shift from London finance to voluntourism? It was quite a dramatic shift, and in true dramatic fashion, I experienced my own road to Damascus moment in South Africa. This happened about six years into my career in London’s financial sector. During a trip there, beyond the traditional safari experiences and stays at beautiful lodges throughout Cape Town and the Garden Route, I participated in building a house for a family in one of the townships. This experience was genuinely life-changing in two fundamental ways. First, it enabled me to interact authentically with local people, gaining real insights into their lives and sharing stories with them – something that had been missing from my previous travels despite being quite fortunate to travel extensively. Second, the satisfaction of helping and making a tangible difference in their lives by providing this family with a proper home was profound. This experience made me realise that I had developed solid business skills but wanted to apply them to something more meaningful and fulfilling. That became the catalyst for establishing what would become Hands Up Holidays three years later. How did you safely visit townships when tourists are typically advised to avoid them? I should emphasise that there are legitimate reasons for caution. I was fortunate to be in the capable hands of my former London flatmate, who had moved to South Africa and become a professional tour guide, developing his own network of trusted relationships there. He was the one who took me into the townships, and I certainly wouldn’t recommend just showing up there independently. While chances are you’d be fine, you need to remain cautious. I should also mention that there’s a concerning trend of township tourism that can devolve into mere voyeurism, which we absolutely oppose. However, there are ethical township visits that focus on the positive developments happening in these communities and provide genuine opportunities for meaningful interaction. How do you reconcile the apparent contradiction between luxury and volunteer work? Luxury and volunteering don’t immediately seem like natural partners. However, when you examine it more deeply, the luxury component serves as the means to facilitate participation from people who want to make a difference but aren’t willing to sacrifice comfort. This certainly isn’t for everyone, but our model is what I call ‘philanthropy volunteering’. The primary benefit comes from the funds our clients bring to projects. If providing luxury accommodations and creature comforts enables those funds to be invested in meaningful projects, then we’re the right organisation for them. Conversely, if you don’t mind basic conditions, there are many other fantastic organisations that will help you make a difference in that way. How do you avoid voluntourism becoming voyeurism? There are two main approaches we use. First, I personally visit every single project we offer, so I can genuinely attest that they’re beneficial and provide real value to recipients, whether communities or wildlife. Second, this connects to my earlier point about different ways to make a difference. People can contribute through time – spending weeks or months at a project – or through specialised skills, like doctors or physiotherapists applying their expertise. The third way is through funding, which is where we excel. We enable our guests to experience projects and gain that meaningful interaction, but their primary benefit comes from providing the funding to build houses, construct stoves, or create accessible facilities, whatever the specific need may be. How do you convince families to choose volunteer travel? I’d argue it’s primarily the parents’ responsibility rather than mine. However, I think it’s important to understand that no one arrives on our trips surprised to discover they’ll be renovating a school. This volunteer component is our fundamental point of difference – it’s what we specialise in and what sets us apart. People only choose us because this is exactly what they want to do. I hope families have these discussions with their children well in advance of booking. What motivates your clientele differently from typical travel agencies? Absolutely, they’re very different. When I first established Hands Up Holidays, I had people like me in mind – young professionals who were cash-rich but time-poor, wanting good vacations while making a difference. However, from the very beginning, we attracted family bookings, which hadn’t been on my radar at all when I was developing the concept. When I asked these families about their motivations, they’d say things like, ‘Our children come from privileged backgrounds, and we want them to appreciate how fortunate they are,’ or ‘We’re seeking a meaningful family bonding experience.’ Many also express that they want to inspire their children to become the next generation of changemakers. So yes, there’s definitely a strong mission-driven aspect in our family clients’ thinking when they make enquiries. Are your clients younger or older than you expected? They’re older than I anticipated. When I wrote the first business plan and brochure, I was targeting young professionals aged roughly 25 to 35. While we do attract some clients in that demographic, I was genuinely surprised by the number of families booking with us. These family clients are typically in their 30s and 40s. How does volunteer travel address overtourism, and what’s the demand? We take a holistic approach to all our trips, with sustainability integrated throughout. While our trips are luxury experiences, we prioritise properties that demonstrate sustainable luxury principles in their design and operations. We recommend restaurants offering organic dishes sourced locally whenever possible, maintain a policy of using only local guides, and choose eco-friendly transport options where available. This approach helps combat overtourism. We also encourage travel to safer but less mainstream destinations – places like Georgia in the Caucasus, Belize, or Roatan in Honduras, which we’re launching in the coming weeks. These destinations aren’t overcrowded with tourists. Additionally, incorporating volunteer components naturally slows down the pace of travel. Instead of rushing from site to site, you’re investing several days in one particular destination and community. How do you ensure controlled growth while maintaining quality over scale? For me, the key is maintaining this as a passion project. I live and breathe this work, and I personally handle all customer enquiries. This isn’t just about passion – I genuinely delight in crafting unique itineraries for our clients – it’s also about quality control. I’m happy that it’s just me managing this aspect, and by virtue of that personal involvement, it naturally limits how much the business can scale. This constraint actually serves our mission perfectly. Voluntourism: Small Is Beautiful and Meaningful The volunteer travel market in which Christopher Hill’s Hands Up Holidays operates represents less than 0.01% of the global tourism industry’s USD 11.7 trillion annual revenue (World Travel & Tourism Council, Future Market Insights). The numbers may look small, but t

AI is radically transforming the B2B sales landscape and accelerating the shift towards intelligent sales enablement. At a major B2B event which took place in Paris in July 2025, I met with Stephane Renger, co-founder and managing director of Salesapps. The leading European sales enablement vendor has placed AI at the heart of its innovation strategy. In this interview conducted at the event, Stephane explains how AI agents are revolutionising commercial efficiency whilst maximising security and privacy. A fascinating dive into the future of AI-powered sales enablement that’s redefining commercial performance standards. AI Saves Time for Sales and Marketing Teams AI-powered sales enablement : Stephane Renger is the co-founder and General Manager of European sales enablement company Salesapps. How is AI transforming sales enablement and sales in general? Stephane Renger: At Salesapps, we’re working on AI agents with the goal of bringing greater efficiency to sales teams, while maximising data privacy and security. Specifically, what do these AI agents do? S.R. We developed three types of intelligent agents for our AI-powered sales enablement solution. The ‘company profiler‘ AI agent analyses the targeted business regarding its strengths, weaknesses, products, competition, news…, The ‘individual profiler’ agent describes the buyer’s profile: background, interests, pain points… Then we use content enrichment agents with metadata to generate sales presentations and pitches, Finally, our ‘conversational agent’ restructures meeting minutes and reports. Once again, this major B2B event took place in the prestigious premises of the Parc des Princes in Paris, with a focus on AI-powered sales enablement. What are the efficiency gains from the implementation of AI within sales enablement? S.R. They are quite blatant, mainly in terms of time savings. Thanks to AI, salespeople quickly access information that used to take hours to research. For a complete sales team, there is at least 20% time saving, which equates to one working day every week. Marketing teams and content managers can save up to 50% of their time. Is this an opportunity for getting rid of salespeople? S.R. No, it’s not. Salespeople only spend one third of their time actually selling. Two thirds are devoted to paperwork, CRM, preparation. Automation frees up their time from what isn’t their core business. Are certain sales roles more threatened than others? S.R. It depends mainly on the products being sold. The buyer only spends 5% of their time with the salesperson, 80% of the purchasing process happens on the web. So the remaining 5% must involve a complex buying process to require human intervention. In other cases, self-service is way sufficient, even in B2B. In a nutshell, Sales Enablement becomes AI-Powered Sales? S. R. For the past two years, we’ve been talking more about ‘AI-powered sales enablement’ than traditional Sales Enablement. This concept is more immediately understandable and evokes innovation in the commercial approach. Worthy of note, for English-speaking markets, we keep that term ‘sales enablement’, but for French-speaking markets, ‘Modern Selling’ is the term of choice. It is more meaningful, especially when discussing AI agent integration, for French-speaking audiences who do not always understand the word ‘enablement’. What can you tell us about reliability and security concerns? S.R. Classic AI models, be it Gemini, ChatGPT, or others are used to research public information. If I want to know who you are or what your company does, there’s nothing better than such a tool that will browse the web, LinkedIn, and other sources to obtain this information. But if I want to process proprietary information, an internal document database, some meeting minutes, an internal conversation, etc., we must ensure data privacy and security at all cost. In this case, we’d rather work with on-premise language models that we can monitor end-to-end. We’ll feed them with this internal information and secure that information. What are your views regarding the future of AI-powered Sales Enablement? S.R. It’s very difficult to predict the future even three to six months from now. Our focus revolves around artificial intelligence. Its performance is increasingly impressive and prices more affordable. Right now, I’m particularly focused on sales coaching and training, and commercial skills development. Simulation and capturing a real-life interview in audio is already possible, but video is still relatively expensive, almost €50 per hour. With the lightning-fast progress in synthetic voices and images, I’m convinced that within three to six months, we’ll be able to offer much more advanced technologies at prices that will allow widespread distribution of this type of agent to sales populations and businesses. In Conclusion: The AI-Powered Sales Revolution These past ten years, Visionary Marketing has written quite a few pieces and white papers on the subject of Sales Enablement. Since then, technological progress and sales team transformation have been lightning fast. This interview with Stephane Renger perfectly illustrates this profound transformation of the sales domain. AI-powered sales enablement is now fully operational, and this technology is redefining commercial efficiency. The productivity gains quoted by Salesapps — 20% for sales teams, 50% for marketing teams — are a sign that something serious is happening now. What struck me at this major B2B event in Paris, was the profound transformation of the market offering in this domain. A few years ago, this side of the water, many Sales Enablement vendors were present, either international or local. In just a couple of years, Salesapps* established itself as the undisputed leader in this sales enablement market in French-speaking countries and is now conquering other markets. The future looks exciting: between conversational AI agents, personalised coaching, and predictive analysis, tomorrow’s salesperson will have tools at her disposal of unmatched power. We haven’t yet seen the end of the evolution of the sales function, and digital technologies are playing a major role in this upheaval. [*Disclosure: Visionary Marketing worked for Salesapps in 2022] The post AI Sales Enablement: 20% Time Savings for Sales and 50% for Marketing appeared first on Marketing and Innovation.

Are AI and developers the world’s best friends or is artificial intelligence a threat to the future of programmers? As artificial intelligence models are becoming increasingly sophisticated, many questions are raised about the future of developers across the industry. Will AI replace programmers entirely, as Eric Schmidt and Dario Amodei are predicting? Will junior developers be facing extinction, as Steve Yegge surmised in a now-famous blog post? Or are we witnessing the dawn of a new era in which technology amplifies human creativity rather than replacing it? I interviewed Nathaniel Okenwa, Developer Evangelist at Twilio, to pick his brains about this question, and his conclusion is that, in the future, software development will undoubtedly remain human-driven even though many changes will occur. The video recording of that interview is available at the end of this blog post. Developers and AI: the Path to the Future of Coding With nearly a decade of hands-on programming experience and a unique perspective on developer community engagement, Nathaniel Okenwa brought both technical depth and strategic insight to this conversation about the evolving landscape of software development. Spreading the Gospel of Developer Tools “My parents celebrated when I got that job title of developer evangelist,” Okenwa said. “I speak and meet with developers, online or in person, and I talk about the tools and the technologies they’re using. A part of this job is being with the community and then spreading the good news of Twilio as well.” AI and programmers, a love-hate relationship? — image antimuseum.com For those unfamiliar with the company, “Twilio is a customer engagement platform and one of the providers helping businesses with their customer support, communication tools, and APIs.” The Junior Developer Dilemma The elephant in the room for the Tech industry is the fate of junior developers. Steve Yegge’s provocative piece ‘The Death of the Junior Developer’ has sparked intense debate, suggesting that AI won’t make inexperienced developers smarter but will enable experienced programmers to eliminate the need for juniors altogether. A daunting perspective for young programmers. Nathaniel offers a more nuanced perspective that challenges this binary thinking . Often, a company doesn’t hire junior developers for their current capabilities. They recruit them because they’re investing in what they will become in the future. Junior developers need to exist if we are going to have mid-level senior developers, developer leaders, and architects at a later time. Nathaniel is right. Programming isn’t just about syntax and algorithms; it’s about developing problem-solving instincts, understanding business contexts, and learning to translate human needs into technological solutions. ‘If you want to create the next generation of builders, then I don’t think junior developers are going to disappear in the long term. We may forget how important they are for a little bit, but they will definitely make a comeback later on.’ The Eric Schmidt Prophecy: Six Months to Obsolescence? The urgency of these questions intensified when Eric Schmidt, former CEO of Alphabet, made bold predictions about the timeline for developer displacement. His assertion that developers would be reduced to merely correcting AI output within six months and potentially eliminated entirely within a year sent shivers down the spines of the programming community. Nathaniel acknowledges the partial truth in Schmidt’s predictions while advocating for a more sophisticated understanding of what developers do. “I think there are elements of truth in it, but I think the situation is a bit more nuanced. AI is, in my mind, another Industrial Revolution. In this context, it means we’ll be looking for repeatable tasks that are extremely simple and how to replace them with technology.” AI and developers: programming isn’t just about writing code, it’s about solving business issues — image of a banker in a large banking institution antimuseum.com The industrial revolution analogy is particularly apt here. Just as mechanisation didn’t eliminate human work but transformed it, AI appears poised to reshape rather than replace programming roles. “I think AI is going to take some aspects of programming and make them so cheap from an effort perspective that it’s not necessarily going to be the best use of people’s time. However, I think developers aren’t just folks that are repeatedly solving minor syntax sentences. They are creative builders coming up with different ways of taking a real-world problem and abstracting it into technology pieces.” AI and Developers: The Abstraction Ladder One of the most compelling aspects of Nathaniel’s perspective is his emphasis on abstraction as the key to understanding how AI will transform development work. Rather than replacing developers, AI represents another rung on the abstraction ladder that programmers have been climbing for decades. Right now, I can use my programming skills to build a website and serve it to millions of people on the Internet. Thirty or forty years ago, I would have needed a whole set of different skills to make that happen. I would have needed so many more hardware skills and so many more specific high-level networking skills. And all of those things have been abstracted away for me to really focus on making this website really fast and performant. This historical perspective illuminates a pattern that AI-anxious people are missing. Each generation of developers has built upon increasingly sophisticated foundations, allowing them to tackle more complex problems without getting bogged down in lower-level implementation details. AI, the printing press and developers. A brilliant analogy by Twilio’s Nathaniel Okenwa — image produced with Midjourney The printing press analogy further clarifies this progression: “If we think about the printing press, at first you needed to have lots of people who would sit down and handwrite a book in order for you to make 100 copies. The printing press came around, and the amount of effort and skills to achieve that shrunk considerably. But you still needed someone who could run that printing press.” The Inconvenient Truth: Not Everyone Ascends However, this progression toward higher abstraction levels raises uncomfortable questions about inclusivity and capability. Not every developer possesses the intellectual agility to continuously climb the abstraction ladder, and there’s value in acknowledging this reality. Nathaniel addresses this concern with characteristic optimism while maintaining realism. “I suppose there will always be people who remain comfortable doing what they are doing in the ways they are doing it. But with technology making so many more different things available, what’s going to happen is users, customers, and the general public are all going to expect more from our technologies and from us.” The market forces driving this evolution are relentless. As AI enables higher-quality experiences at scale, customer expectations rise accordingly, creating pressure on all technology providers to evolve or risk irrelevance. “The folks who aren’t meeting these higher standards of experiences will not be able to deliver the value that their customers and employers are expecting from them. If they don’t continue to meet that bar of expectation that is growing higher and higher, especially as AI helps people to develop new ways of doing this, they will be left behind.” The Digital Transformation Paradox This raises an interesting paradox about digital transformation that I’ve observed throughout my career in technology consulting. Thirty years ago, we predicted that traditional industries like banking would be disrupted by digital-native competitors. Yet established banks have largely survived, adapting gradually while maintaining their market positions. Nathaniel offers an insightful perspective on this seeming contradiction: “It didn’t kill banks, but I would argue that even if maybe they took a while to get there, the way we interact with our banks is completely different from the way we interacted with banks when we were younger. There are 18-year-olds who have no idea what a chequebook is.” The transformation happened, but more gradually and less dramatically than predicted. This pattern suggests that AI’s impact on development may follow a similar trajectory—profound but evolutionary rather than revolutionary. The GitHub Co-pilot Paradigm: Integration Over Replacement Perhaps the most practical insight from our conversation concerns how AI tools are being adopted by developers. The success of GitHub Copilot and similar tools demonstrates that integration beats replacement as an adoption strategy. “Sometimes there are engineers who are reluctant to use AI or don’t want to go out of their way to bring AI into their workflows. But when Copilot came out, when other tools that have that technology built into the applications, the interfaces they are already using, the adoption increases significantly.” This observation reveals a crucial truth about technology adoption: the most successful innovations enhance existing workflows rather than demanding entirely new ones. The future of development tools lies not in replacing programmers but in making them more effective within familiar environments. The Copy-Paste Continuum One of the most honest moments in our conversation addressed the reality of code reuse – something every developer practises but few discuss openly. The fear that AI will turn programmers into mindless copy-paste operators misses the historical context of how developers have always worked. “Copying and pasting has been an integral part of the engineer’s journey for decades, and it’s not going anywhere soon. Even if we are copying and pasting from a d

How do luxury brands maximize experiences in sports events? I attended the 2025 Monte-Carlo Masters, which showed a strong presence of elite brands fighting for high-end customer engagement. Brands such as Rolex, Sergio Tacchini, and Replay can be found advertised almost everywhere at the famous tennis tournament. These brands use the values of this tennis tournament’s identity, which are class, prestige, excellence, and exclusivity, to reinforce their brand image. In this article we will be looking into the strategy behind premium companies and their connection to the Monte-Carlo Masters Tennis Tournament.  Luxury Brands Maximize Experiences in Sports Events This photo was made using Midjourney and Adobe Photoshop. Sports Sponsorship in Luxury Branding Luxury brands have had a history of gravitating towards sports such as tennis, golf and equestrian sports because these sports emphasized precision, elegance, and tradition. Brands saw that it seemed like a good fit for their deluxe identity due to the traditional affluent audiences that these sports offered. Only the best of the best athletes competing at these events align with the values of the most luxurious brands that they are the best of what they do. These brands are able to prolong their exclusivity while opening up visibility to sports viewership. As brands become bigger and sports viewership grows, stylish brands are opening up to collaborations with bigger sports that may not have as much class or prestige, such as football and basketball.  Strategic Brand Positioning at the Monte-Carlo Masters What once was known as the Monte-Carlo Masters is now known as the Rolex Monte-Carlo Masters. Rolex has positioned themselves front and center at a prestige tournament. Not only are they in the title of the tournament, they are on the logo and can be found everywhere at the tournament itself. Another brand that has strategically positioned itself is Sergio Tacchini. Being at the tournament itself, it is impossible to miss; every ball kid and many employees working for the tournament wear a piece of clothing from Sergio Tacchini. Just being at the tournament, you are constantly being advertised to, whether you realize it or not; everywhere you look, you are reading another brand name. Other brands, such as Maserati and Emirates, help back the elitist and prestigious image of the tournament. Monaco, home of the tournament, is known for its wealth as well as its opulent residents, one more reason to advertise an elegant brand, as the target market is mainly wealthy individuals. “According to the World Population Review, Monaco is the richest country in the world in terms of GDP per capita and is regarded as the “billionaires’ playground.” Celebrities and top-level athletes being at the tournament make being at the event feel like it’s only for those of wealth, class, and elegance.  This photo was made using Midjourney and Adobe Photoshop. Brand and Customer Experiences  Some of the most exclusive experiences at the Monte-Carlo Masters are sponsored by posh brands. VIP lounges and luxury suites are curated for high-end customers and guests. Additionally, behind-the-scenes access, meet-and-greets with athletes, and fancy gifting moments allow brands to showcase their exclusivity even more to only those that can afford them. Hospitality packages include gifts, discounts, special access, and events made to feel extraordinarily classy.  The Société des Bains de Mer (SBM), which is responsible for venues at the event, creates gourmet dining opportunities as well as private lounges mimicking luxury brands. Customers at the Monte-Carlo Masters are rewarded just by being at the event itself. These rewards include access to limited edition merchandise, entries to giveaways or raffles, and the opportunity to use the VR Tennis simulator. To further show status of class and order, boutiques at the event are limited to a certain amount of people at a time to prevent cluttering. When a customer buys a ticket for the tennis match, they are not just coming to watch one game, they are spending practically the whole day there. Even in between matches there are activities to be done around the venue. These activities include, finding something to eat (there are a lot of choices), VR tennis simulator, walking around and exploring the area, shopping in the countless boutiques and tennis stores. Scarcity and “Limited Edition” The value of going to a sports event comes from the electric anticipation of not knowing what will happen. Fans come to witness firsthand the action and to purchase limited edition products showing they were there. Rolex and other brands offer merchandise exclusive to the event itself, signifying someone was at the event. A piece of limited edition merchandise to show you were at the Rolex Monte-Carlo Masters is also an advertisement every time you wear it in public. Short-term promotions and exclusive collaborations build a sense of urgency used to encourage customers to buy their product. Brands use this to drive up their exclusivity, giving only people that were at the event a chance to purchase something that will remind them of how special that moment was.  This photo was made using Midjourney. Content and Social/Digital Media Social media has completely changed this world as we know it, and that is not only limited to the social aspect, but it has changed the business world drastically. Content creation is a great way to gain publicity, and what better place than a sports event to promote your upscale brand? Brands such as Replay and Malongo took advantage of this event sponsorship and made social media promotions showing their collaboration with the renowned event. Rolex and Tennis Rolex has been partnering with tennis for 46 years, since 1978. Made with Napkin AI. Key Statistics about Luxury Brands in Sports Events These statistics show that the tournament continues to improve their technology and assets. Furthermore increasing their brand identity relating to top class. Maximizing luxury brands customer engagement in sports events: facts and figures about the 2025 Monte-Carlo Masters – infographic done with Canva Conclusion Classy, lavish brands strive to take advantage of events such as the Monte-Carlo Masters tournament to build brand identity and to increase publicity. The Monte-Carlo Masters serves as a sort of “playground” for luxurious brands to strategize, promote, and attach themselves to the values that the event portrays. Brands that strive to align with excellence, class, prestige, and elitism promote themselves using the Monte-Carlo Masters to represent these traits. These companies take advantage of the tournament knowing that the audience is generally wealthier. The post Luxury Brands Maximize Experiences in Sports Events appeared first on Marketing and Innovation.

If you are dying to understand the various GenAI prompting methods, how AI interacts with your prompt, and why this is key to optimising your results, this free prompting guide was made for you. This manual describes GenAI chatbots and the different methods of prompting. It was put forward by Frederic Cavazza, a digital transformation expert, consultant and speaker with over 25 years of experience. A Free Prompting Guide for Aspiring GenAI Experts This free GenAI prompting guide written by Frederic Cavazza was translated and adapted by yours truly. I’ve known Frederic Cavazza for years and I’ve even had the pleasure of working on a few engagements with him. As we were on our way to a GenAI client workshop a few months ago, he showed me this guide and I thought to myself: “This is exactly what I’d like to share with my readers and students”. Hence this translation and adaption of Frederic’s prompting guide, with his kind permission. I tried his tricks myself and I can guarantee that the mega prompt he describes at the end of the guide is really something you should test, copy, paste, adapt and keep in your own prompt library. A GenAI Guide about the Art of Prompting Artificial intelligence is booming, and chatbots like ChatGPT are radically transforming the way we interact with digital tools, changing the way we work. This guide aims to introduce you to the art of ‘prompting’, a key skill for engaging effectively with these artificial intelligence platforms and making the most of their potential. If you’re researching a topic on the Web and you type in a simple key phrase, the result may not be very compelling. On the other hand, if you structure your search well, you’ll get more relevant answers. And so it goes with artificial intelligence tools like chatbots or digital assistants. Frederic Cavazza is the author of this great prompting guide entitled the ABC of prompting – photo portrait by antimuseum.com The more structured the prompt, the more relevant the outcome GenAI Prompting? The way you ask AI chatbots questions or give them instructions is conducive to more or less convincing results. This is what is called ‘prompting’, i.e., the art of formulating clear and precise instructions to guide the work of artificial intelligence models. In essence, a well-structured prompt is like a well-formulated search query. When done properly, it shall provide relevant results. There is no one-size-fits-all prompt methodology, as use cases differ from one user to another. However, we recommend you use one of these three methods based on your needs. Three Recommended GenAI Prompting Methods These three methods are entitled RTF (Role, task, format), CRAFT (Context, role, action, format, tone of voice) and COAT-SITES (context objective, acumen, task, specimen, impediments, tone of voice, encoding, scrutiny). Each technique works best depending on expected results. RTF was made for quick results, CRAFT, for simple questions with more accurate results and COAT-SITES, for clear cut questions and extensive results. So, what are these methods about? Here they are in more detail. 1. RTF Method With RTF, the prompts specify the role, task and format that AI should adhere to. It consists in a simple, “you are…, you must…, your answer must…” Role indicates who the AI bot should impersonate, providing a contextual framework. Task, gives AI the precise action or problem to be solved, guiding AI towards the expected objective. And Format specifies the type and structure of the outcome. 2. CRAFT Method Should you be looking for more accurate results, it might then be a good idea to expand your prompt to incorporate more context. The CRAFT method is therefore what you would have to resort to. CRAFT implies providing specifics to the AI chatbot in your prompt such as, “I’m in charge of…, you are… you have to…, your answer should include…, choose the following tone of voice.” With the CRAFT method, Context describes the overall situation or requirement. Role, tells AI the character it should enact. Action, specifies what AI must do, directing the LLM. Format, provides examples or details clarifying final expectations. Tone of voice, defines the expected style or category AI must follow, aligning your response with your objective and audience. Expanding your prompt to formulate a better structured and accurate result. 3. COAT-SITES Method In the case of COAT-SITES technique, your prompt is not only expanding the context of the situation but giving AI strict guidelines to narrow the margin of misunderstanding. Allowing for your results to be more accurate and extensive. This includes Context, Task, Tone of voice, as in the previous methods but also includes Objective, Acumen, Specimen, Impediments, Encoding and Scrutiny. Objective and Acumen, give AI the tools to reach your expected result with the correct level of expertise. Specimen and Impediments, provide clear examples and guidelines of what is wanted and what should be avoided. By providing models or illustrations, you clarify the expectations, just like defining what cannot be done narrows down your result. Lastly, COAT-SITES encompasses Encoding and Scrutiny. Encoding defines the output format syncing the results to your objective and scrutiny offers a final sanity check to ensure the results comply with your stated guidelines.  Test Drive the Prompting Methods Once you have familiarized yourself with these three prompting methodologies, give them a go. Here are some tips and tricks to keep in mind when navigating GenAI chatbots. Frederic details them all in the guide for you. After you have signed in to a chatbot, enter a few questions into the prompt window to get a feel for how it replies. After you’ve done that, try testing out the suggested prompting methods, saving a specific topic or tricky task for COAT-SITES. Tips and Tricks When interacting with your favourite chatbot, remember to select relevant keywords, stick to one question at a time, test and tweak your prompts and follow up. Don’t settle for half-baked answers and consider asking a different chatbot to critique your results. Lastly, remember at all times that the better formulated your prompt, the better AI can provide accurate and relevant results. So give these methods a test and see how your interaction with GenAI chatbots evolves. Download for Free the ABC of Prompting for Aspiring GenAI Experts by Frédéric Cavazza The post GenAI Prompting Guide for Aspiring Experts appeared first on Marketing and Innovation.

How is AI Search changing the Internet and what role are we playing in this transformation? In this article, I discuss the current state of adoption of AI-powered search engines. By reflecting on the perspectives of Kevin Roose, Matteo Wong and Joanna Stern, this piece explores what we gain—faster, more organized access to information—and what we risk losing—the diversity of sources, depth of content and our curiosity to go beyond a single answer. Breaking Up With Your Traditional Search Engine How is AI Search changing the Internet and what role are we playing in it? — image generated with Canva and ChatGPT Is it time to ditch Google and your other favorite search engines? In the past few years, AI has disrupted numerous industries in the digital sector, but arguably one of the most noteworthy shifts has been in the online search market. Think of the last time you searched the internet for information—did you sift through pages of websites, or did AI place the answer at your feet?  The decades-long reign of Google might just be challenged by this new age of conversational and contextually aware search power.  Three Voices on AI Search: Roose, Wong and Stern To examine this idea more deeply, this piece will consider three different articles written by Kevin Roose, Matteo Wong and Joanna Stern. As the conversation surrounding AI evolves, their observations offer unique points, from skepticism to adoption, reflecting the considerable development of AI capabilities and increasing adoption by users.  By breaking down their findings and looking at the numbers of adoption, I will explore the current and future landscape of AI-powered search. So whether you’ve already hitched your ride to the AI bandwagon or are still clinging to your Google tabs, here’s a glance at where our process of search, the internet, and information is headed.  AI-Search at the speed of light — Photography by antimuseum.com Kevin Roose: Continuing with Caution In February 2024, Kevin Roose wrote an article for The New York Times titled “Can This A.I.-Powered Search Engine Replace Google? It Has for Me.” As you might have guessed from the title, Roose’s experience was a positive one, but not without some hesitation. To test his theory, Roose gave up Google, instead opting for Perplexity, an AI search engine founded by former OpenAI and Meta researchers. Roose’s several-week adoption of Perplexity left him sufficiently convinced AI search engines were a valid competitor against traditional web browsers, but adjustments were needed if they are going to win the race.  The information retrieval and contextual understanding offered by AI proved more useful for the majority of his work. However, due to AI’s limitations, Google was not obsolete. Acknowledging the absence of credible sources, real-time updates, and the occasional lack of truth AI provided, Roose found his usage of AI had certainly become more prominent, but most successful when used alongside Google. The article suggests the adoption of AI will not be a bold movement, but a gradual and natural shift in user behavior. Still indecisive on the effects AI will have on journalists, publishers and others who create the internet landscape, Roose stated, “I’ll have to weigh the convenience of using Perplexity against the worry that, by using it, I’m contributing to my own doom.”  Matteo Wong: Exploratory Search Roose is far from the only one to have concerns about the growing popularity of AI. The Atlantic’s Matteo Wong placed a heavy critique on AI in his article “The Death of Search.” Wong’s piece focused less on the way in which a person uses AI and more on the way that AI changes our relationship with information. Should you cross traditional Internet Search off the list? Stern’s answer is a resounding YES ! – image generated with ChatGPT   In his view, the concern is not AI’s credibility or factuality—those issues could be fixed as systems evolve—but the loss of an exploratory model of search. When people stop engaging critically with information, they lose the ability to evaluate and explore their own curiosity.  He states, “It could completely reorient our relationship to knowledge, prioritizing rapid, detailed, abridged answers over a deep understanding and the consideration of varied sources and viewpoints.” The indication of Wong’s argument is that by extinguishing that exploratory model of search and making information “too” accessible, it dismantles the fundamental idea of the web.  Joanna Stern: Embracing Convenience  In opposition to Wong’s take on the adoption of AI-powered search engines is Joanna Stern, who shared her full support in her New York Times article, “I Quit Google for ChatGPT—and I’m Not Going Back.” Stern’s piece rings similarly to Roose’s in that once she made the switch, the probability of going back was unlikely. Trying a variety of AI platforms, Stern found the ease and refinement of AI a refreshing break from sponsored links and promoted products offered by Google. Only in searching for a known product, website or article did Google still prove useful.  While she noted AI is consistent with the limitations of poor sourcing and inaccurate information, Stern’s main concern was the loss of visibility and traffic for the information’s original source.  What’s to keep AI from making these websites and publications obsolete, and who do you credit for the information you got? Stern wraps her argument into a neat bow by saying, “So, yes, I’ll encourage you to try AI for search, as long as you promise to click a link when you can.” My Experience with AI Search While I have familiarized myself with the platforms ChatGPT and Perplexity, my experience with AI-powered search engines is still limited. However, from what I have seen, I am impressed. The concise, summarized answers leave me satisfied and often without lingering questions. Still, despite the efficiency, I have found I do not stray far from Google. I am not sure if it is a habit or precaution. Looking to the Future  So where do you stand? Are you ready to commit to AI, or is apprehension holding you back? As each article shows us, the level of adoption is varying, and chances are you’re somewhere in the middle. But there’s no doubt the way we access and receive information is changing. The worldwide market size of AI jumped from approximately $50 billion to $184 billion in just one year. Additionally, a survey by Activate tells us the number of adults in the United States using AI first for their online search was around 13 million just two years ago and is projected to reach 90 million by 2027. The growth is telling, and it’s not limited to one platform. ChatGPT, Perplexity, Copilot, Claude—even Google is trying to reinvent itself with Gemini. So whether you’re a curious newcomer, cautious observer or full-on convert, it’s clear we are stepping into a new age of internet. Moving forward we will have to decide if the gains outweigh the losses and with continual adoption, new questions arise. Will AI search enhance or limit access to diverse perspectives? How much of a role will it play in our daily lives? I guess we will have to wait and see. AI search is taking Internet search a level higher — photo by antimuseum.com The post AI Search : Breaking Up With Your Traditional Search Engine appeared first on Marketing and Innovation.

Let AI handle the chores, and humans do the thinking: such should be the future of content marketing. In this piece, I try and debunk a few myths. Firstly, generative AI  can be creative — and often is. Secondly, AI doesn’t necessarily make us stupid; we don’t need it for that. And thirdly, becoming a prompting Guru isn’t necessarily the key to producing great content. The question of AI’s role in content marketing is actually more strategic than technical: it’s about why and for whom we create content. This is the major issue at stake for today’s and tomorrow’s marketers. In this presentation, I urge readers not to outsource their thinking to AI, and rather offload the chores of low-value tasks to machines. Unfortunately, it should be noted that they aren’t always doing a good job with that. Chores to AI, Ideas to Humans Since the machines started thinking, we’ve had more time to do the dishes, wrote Joanna Maciejewska. Like her, I’d rather it were the other way round. TL; DR Ms Bernard is an SEO agency avatar who adds links to Visionary Marketing on “her” website. Her “work” raises some fundamental questions.  Criticisms aimed at AI often miss the mark and overlook fundamental issues: why we write, for whom, for what purpose… We also dismiss a few myths such as ‘AI can’t be creative’, ‘AI makes us stupid’, and ‘mastering prompting is a silver bullet’. Hence, the question of AI’s role in content marketing is more about strategy than it is about tech. In this presentation, I urge content creators (and readers alike) not to outsource their reasoning and to leave the chores to AI. This piece owes a lot to Ms Joanna Maciejewska AI and Marie Bernard, the e-commerce Queen Ms Benard is adding links to Visionary Marketing. She is very nice but unfortunately she isn’t a real person. Let me introduce you to Ms Marie Bernard. This pretty young woman, somewhat artificial in appearance, exists only in Midjourney’s archives and on the website of “her” SEO agency. This supposed e-commerce expert found herself embroiled in a semantic mix-up that was both amusing and revealing. Taking inspiration from one of my articles, this visionary author mixed up ‘snow globe’, an expression used by one of my expert interviewees as a metaphor, and ‘snowball effect’. Thank God, she inserted a link to Visionary Marketing so that I could correct that fatal mistake. Far from being trivial, this anecdote raises a few fundamental questions. Who is writing? For whom? How? And for what purpose? In fact, it even poses bigger questions such as “what is humans’ place in society, and what sort of society do we want for our children and children’s children?” AI Information Overload  Content about generative AI is so ubiquitous that we have gone past information overload. AI content analysts are skirmishing via X (formerly Twitter) and LinkedIn posts, mainly on the technical front (this AI is better than that one), creativity (AI produces interesting ideas or rather, is dull and inferior to humans), and usage (“download my ultimate prompting guide!”). Yet all these debates (and sadly others that are less prevalent, like the poorly documented issue of energy consumption) fail to address other key questions: who are we creating for, why, and for whom do we work — or more broadly, what kind of society do we want in the future?  Generative AI at the Heart of the World’s Issues  AI, and in particular generative AI, have generated most of the noise on social media, blogs, newsletters, and chat around the pub. Traditional economy seems to be ignoring the phenomenon or treating it as incidental — a recurring habit when it comes to digital innovations, but online debates live on unabated.   Whether and how we should use generative artificial intelligence is now a central question in our modern societies, and that’s understandable. Machines have been able to play around with text since the 1950s, but computing power and large-scale training on such a vast and decent dataset — despite criticisms — have never been so strong. In recent weeks, engineers in London have even shown how two AI bots can talk to one another. Even if it’s only a demo, we’ve known since the early 2000s that machines can buy and sell stock (algorithmic trading roughly amounts to 60-75% of total trading in the most developed markets, and this was already true back in 2006 when I worked in that field). So, why shouldn’t an AI known as “agentic” buy train tickets?  Hence these legitimate questions.  A machine capable of writing “like” humans? The fact that a programme — literally a “machine” in the sense of a computer — is capable of writing like humans, or nearly, is disconcerting.  *[Machine] A mechanically, electrically, or electronically operated device for performing a task first entry from Merriam-Webster What’s even more unsettling is that humans often write more poorly than machines. This is what Loubna Ben Allal, a researcher at Huggingface and an expert in training generative AIs, describes in a video on the underscore channel, which is worth watching. She explains how content is filtered during training sequences and, surprise, surprise, she says that good Ai-generated content is often better than bad human content. Sadly, poor human content is everywhere.  Note that there are also texts, 100% AI-generated, aimed at proving that Loubna is right.  A text designed to show that separating the wheat from the chaff in content creation is a non-issue. Unfortunately, it was written by an LLM. Language, an operating system?!  If these mock texts are so disconcerting, it’s because language and the written word are indeed some of the fundamental characteristics of the human species.  In the beginning was the word. Language is the operating system of human culture. Yuval Harari — NYT March 2023 Yuval Harari, with a kind of reverse anthropomorphic twist, even calls it the “operating system of human culture”. Despite this idiosyncrasy, Harari is zeroing in on the real issue. The real core problem isn’t technical, but deeply philosophical, especially when the most famous generative AI tools are led by a maverick who’s trying all he can to put us in a Spike Jonze film. Ultimately, philosophy could or should redefine how AI is trained, explain Michael Schrage and David Kiron of MIT Sloan Management Review. The Real Problem With So-called Generative Tools The real problem with these generative tools isn’t technical, nor is it about creativity or even how well one uses the tool. It’s more fundamental, relating to the very essence of work and, more broadly, of human societies. Whatever human shortcomings and flaws there may be, and they are indeed numerous.  This is all the more important, given discussions about new tools such as Manus, which promise even more autonomous intelligence capable of “agenticity”, a direction that appears to be a goal for many of the creators of these programmes.    Generative AI is going to vanish? Really… There’s no point in playing down generative AI, as I saw here and there, by predicting their demise (you don’t just eliminate tools that the whole world has made their own, no matter how imperfect), nor in overestimating their potential (there are simply too many tools and possible uses).  Denying how astonishing these tools are is pointless. Likewise, describing LLMs as “stochastic parrots”, is no longer relevant. It used to be apt, barely two years ago. Yet, that’s no longer the case. Safety nets exist, the biggest pitfalls (such as asking ChatGPT to prove that the Earth is flat) as former Apple Siri cofounder Luc Julia claimed recently in a Swiss daily are old hat. The right way forward is hybrid systems combining the power of LLMs with more conventional computing. It’s a matter of time before this merger is done and it might not even take too long. Whoever has witnessed the development of IT and the Web over the past 40 years knows it takes time to innovate. Time is of the essence. Hence, even though the results we get today are still often disappointing, patchy, or downright wrong, GenAI models of 2025 hallucinate far less than they used to, provided you pay and pick your model carefully. You may check for yourself with Perplexity.ai, which will answer your question on this subject while delivering links (sometimes off-target, so you’ll still have to cross-check that information).  In short, four breakthroughs occurred from 2024 to 2025 in this field:  Reduced error rates from 1 to 3% thanks to techniques like Retrieval-Augmented Generation (RAG), drawing on existing documents.  Model improvements including the inevitable OpenAI, with its GPT-4.5 model, and others (I particularly recommend Claude.ai). Innovative methods like “deep research” or “chain of thought”, often flawed and slow, but give them time and they will improve dramatically.  Checks and adjustments: Tools like “Automated Reasoning Checks” introduced by AWS have been designed to detect and correct hallucinations before production use. Still, hallucinations remain common and won’t vanish soon. Again, it will take time before all control mechanisms are in place. Chain-of-thought is one example: it’s still a bit awkward, but it gives a flavour of future possibilities. That said, even if I’m not a big fan of AGI (see the following article), generative AI challenges human skills and abilities and as a consequence of that, our very place within society.  Three directions for deeper exploration Essentially, there are three areas that need to be investigated. First, our capacity to be truly creative. Second, AI’s impact on our cognitive and intellectual abilities and finally, there’s the question of usage. 1. Let’s start with creativity Obviously, one could wonder whether GenAI is creative or not. But above all, this very question challenges us, humans. Thus, the real question should read: are humans any more creative than GenAI? The answer isn’t straightforward, even if that may come as a surprise. One

Isn’t the notion of “disruption “, aka disruptive innovation, used and abused by analysts and technology experts? And by dint of abuse, aren’t we in the process of deluding ourselves? At a time when some are fretting about the volatility of the business generated by ‘unicorns’ or even centaurs, it is perhaps worth asking whether we have not entered an innovation bubble, yet accentuated by that of generative AI, marked by the correction of technology values and a return to more traditional values. Yet it may be too early to find out about the reality of such disruptive innovations. Here are my thoughts about the subject with a few references to sources and books I found interesting. Disruption: Is Disruptive Innovation Overhyped? I find reviews of supposed disruptive innovations in the media, and especially social media, somewhat lacking consistency. One minute everyone is vowing that a revolution has happened. The next that a bubble is about to burst, yet no one is able to predict the future properly. Thus, is disruptive innovation real or a pie in the sky, or does it emerge over time? Is, by and large, IT causing disruption in our lives, or are there more important thing on earth? In short, how can we ensure that our vision for innovation is accurate? – image produced with Midjourney The so-called GenAI revolution While some have been claiming that we are living in a bubble of innovation (here, here and here for instance and here and here with AI), it has to be said that not everyone always agrees. Especially with the advent of the so-called GenAI revolution. I’ve been asked whether electric cars were a disruptive innovation. For those of you who don’t know the history of innovation, let me introduce you to the “Jamais Contente (“Forever unsatisfied” literally), which broke the 100kph speed record near the Fulmen factories in Saint-Germain-en-Laye, France in … 1899 [photo in public domain]As I felt like tackling the topic of disruptive innovation, I thought it would be interesting to revisit an article by Joanne Jacobs from a few years ago about this subject: ‘Are we in a disruptive bubble?‘. In this piece, she explains what role disruptive innovation is playing in contemporary markets. She argues that disruption is not just a fad, but something more profound. Forget all about unicorns, here come the centaurs! Bessemer Venture Partners – State of the Cloud 2022The hype surrounding disruptive innovation is overwhelming. Here is what I found here and there: Disruptive innovation is deemed to impact businesses and employment . with all-out automation a major source of job destruction; Integration of productive innovation is supposed to have enabled some companies to reinvent themselves ; Organisations are said to be reshaped through the introduction of collaborative networked business approaches ; Profound changes in traditional markets (as for banks for example). A spanner in the works Despite this, and the spectacular performance of some companies that have established themselves in just a few years to the point of throwing a spanner in the works of well established markets and provoking defensive reactions, some observers maintain that we are facing an innovation bubble. Disruption: bubble or not bubble? – image Midjourney And these same observers point out that the expectations they have of these disruptive innovations are not in proportion to what they could deliver. And when expectations exceed what innovation can deliver, disappointment occurs. As described by Gartner in its “Hype Cycle” with what the US analyst group calls “The trough of disillusionment“. Here the Gartner Hype Cycle of 2008 technologies And the 2021 update. In the meantime many of the key groundbreaking technological innovations of the 2000s have fallen by the wayside, to be replaced by other, more trendy ones. With AI at the height of the current craze and without Web 3 (even Gartner have given up on it even though they wrote a favourable report on it). Disruption strategy: not just a buzzword “The reality is that business disruption is not a fad. It is not a set of buzzwords you need to use in planning meetings, and it is not a way of positioning a brand in the marketplace. ,” explains Joanne Jacobs. In her view, the only real break is the one that results from the convergence of three elements: Emerging technologies; Changing customer needs; The availability of resources. It is the combination of these three ingredients that she believes makes disruption a reality or a fiction. Disruption is the result of risk-taking. Often, it means that you should be making the most of a legal loophole. We could, however, add a few important ingredients to this recipe: Significant market share to the point where it weighs on the incumbent players (in mass market, for a market share to be stable, the bar is set at 20%, with dominant products often achieving 70 or 80% in mature markets); A valuation that is not based solely on market cap (by its very nature volatile and speculative, with recent unicorns being punished for being valued at up to 50 times their sales, which is unreasonable); The ability to make a lasting mark on a market by changing practices, evolving buying patterns – even society and lifestyles. And lastly, the ability to survive market re-regulation, as was the case for ecommerce with Amazon. The Seattle firm, for example, sold VAT-free until 1996 in the UK (a little later in Europe). Re-regulation did not kill Amazon, it continued to thrive for many years. A second tier re-regulation is happening now with the implementation of VAT for all vendors on marketplaces. Let’s challenge the challenge  In recent years, we have seen the emergence of new entrants in markets that were thought to be stable and saturated: “AirBnB entered the top ranks in terms of hotel market capitalisation and Uber represented the world’s fastest-growing car rental with driver service,” Joanne wrote in 2015. These businesses were seen as a real challenge to such established markets.  But what is the situation today? There was a clear wake up call in the high-tech industry. No more valuations without sound business results underpinning. Well, maybe. Here’s to disruption – the 1880s according to Vaclav Smil – Numbers don’t lie – p 98. So the question arises, is disruptive innovation overhyped? Vaclav Smil, the famous author of “Numbers Don’t Lie” answers bluntly that we are mistaken. According to him, the most innovative period in human history was the… 1880s ![/caption] According to the worshippers of the e-world, the late 20th century and the two opening decades of the 21st century brought us an unprecedented number of profound inventions. But that is a categorical misunderstanding, as most recent advances have been variations on two older fundamental discoveries: microprocessors […] and exploiting radio waves, part of the electromagnetic spectrum. Smil, Vaclav. Numbers Don’t Lie (p. 97) A growing bubble of innovation? According to Smil, and others, we may be living in a context that reflects a flowering of innovations, an accumulation of gadgets that are more or less important or distracting, but in which we are unaware of the importance of the underlying innovations. The mobile: cause for wonder or plain incremental innovation? To mimic smil’s deliberately cursory demonstration, we marvel at our little computer phones, but fail to take into account the importance of the work of Nikola Tesla to whom we owe the industrialisation of alternating current. Tesla died in debt and lonely, but without him, none of these gadgets would exist! Amazing innovations, real breakthroughs? Many of the innovations we use are undoubtedly incredible – and I never cease to marvel at those communication tools we wield. Yet, does that mean that all these contraptions are truly disruptive? Reading this article from 2015 today as the clouds gather over tech stocks and others are towering up is interesting. Where do we stand on “disruption” at a time when, as Smil has it, there are many more important things than that in the economy. A disruption bubble or a hyperbole of disruptive innovation? In 2015, “[…]A whole range of disruptor companies from DropBox and SurveyMonkey, to the secretive Palantir Technologies and audacious SpaceX”, were redefining the way organisations were communicating, researching and developing products, Joanne explained. Even then (2015 seems a long time ago) she was rejecting the idea that we were living in an “innovation bubble”. At the very least, she recognised “a bubble of disruption hyperbole”. 30 years after the development of the commercial Web, we have the necessary hindsight to see what has really changed under the impetus of these ‘disruptive’ companies. And I have miwed feeling about the result. Both naysayers and proponents of disruptive innovation mays disagree with me, though. Regardless, I have looked at both sides of the equation, and the pros and cons of that so-called disruption. Signs of evidence of disruption According to Eric Van Susteren (Momentive’s head of Brand Content strategy), there are 5 pieces of evidence that this disruption exists: The Great Resignation could be the proof of a real and profound change, even if it is not solely driven by technology; This very big resignation have brought to the forefront employees’ expectations in the areas of diversity, equal opportunities and inclusion; A majority of new IT purchases were sourced from new suppliers; Nearly half, of (US) consumers say they are buying more online today, even though the ecommerce boom appears to be over including payment innovations that have fizzled out; The boom in the use of digital continues unabated with consumers ever more inclined to use online services. Better still, McKinsey proved to us back in 2019 that the pace of disruption was accelerating in its report “navigating in a world of disruption“: Disruption is accelerating according to McKi

Growth hacking can often be perceived as toxic, but you can sit back and relax, it is possible to practise ethical growth hacking but it requires time and energy, growth hacking expert Frederic Canevet explained to Visionary Marketing. In a nutshell, it may be a little harder than you think, but it is well worth the effort. Fred, who ate his own dogfood to sell his bestseller on the subject, tells us everything we should know about whte hat growth hacking. Ethical Growth Hacking Is Not an Oxymoron White hat, back hat? Growth hacking often suffers a dire reputation fuelled by unscrupulous individuals, some of whom have built real fortunes on questionable approaches. But ethical growth hacking is possible, explains Fred Canevet – image created with Midjourney on our personalised mode. Could you mention historical examples of growth hacking? Frédéric Canevet: There are two tale-telling cases that illustrate the controversial practices of growth hacking perfectly: In America, Airbnb got its start by exploiting data from Craigslist. The company developed an automated system to extract property listings and contact owners, offering them the chance to earn $500 a week by listing their accommodation on Airbnb. In France, the founder of Telecom operator Free Mobile Xavier Niel, back in the days of the Minitel, created a tool to send automated mass messages to Minitel users. Lonely hearts messaging services on the Minitel being most profitable at that time, he launched a competitor to a leading dating service and diverted their traffic through targeted messages. Although this practice earned him legal action and a lost court case, the profits generated helped him build his initial fortune, notably through a network of sex shops linked to this Minitel business. Can Growth Hacking Be ethical and responsible, though? FC: Yes, it’s feasible but it requires time and effort. Ethical growth hacking: white hat ends up paying better than black hat – image made with Midjourney on our custom mode. How should our vision of growth hacking evolve overtime? FC: Our approach has to evolve considerably in the face of today’s economic challenges. In a tense economic climate, we can no longer afford traditional marketing with its long-term plans. This is precisely what inspired growth hacking in Silicon Valley, where startups had to, as the time-honoured slogan went, “live or die“. In a world tending towards the end of consumerism, at least in Europe, the challenge is to do more with less. There are three levels of growth hacking. “White hat” represents legal and ethical practices, similar to the “Fosbury flop” in athletics – a revolutionary innovation, but one that abides to the rules. This approach is based on business cycle analysis using the AARRR method: Acquisition, Activation, Retention, Recommendation and Revenue. “Grey hat” is sitting in the middle. For example, automation on LinkedIn, although prohibited by the platform, is still widely practised. I have personally experienced the risks of resorting to this approach when I was suspended for managing two separate profiles. Finally, “Black hat” encompasses strictly prohibited practices: i.e. creating fake accounts, identity theft, or unauthorised recovery of personal data. These methods may seem tempting in the short term, but prove disastrous for a company’s reputation and long-term survival. How can we guarantee efficiency while remaining ethical? FC: Sending mass unsolicited messages in LinkedIn serves no purpose. Instead, effectiveness lies in forging true connections. The strategy I adopt lies in the daily publication of high added value content, demonstrating real expertise. It’s not an aggressive sales approach, but rather inbound marketing based on trust. In fact, email spam is a no no. You send 10,000 emails and what you get is a 0.5% open rate and a slightly lower click rate. All in all, as you sent tens of thousands of messages, you may get some sort of result. But very soon, all this is bound to dwindle. Not to mention how damaging all this could be to your reputation. As for ‘black hat’, I absolutely forbid it. In particular, fake accounts attached to the name of a company, solely for the purpose of recovering data from lists of people and companies that follow the page of the target company. This is illegal, because it’s identity theft. The same applies to those individuals who seek to recover the email addresses or telephone numbers of people with whom they have no relationship. I refuse to do that, especially as it often involves personal data. Facts and Figures About Ethical Growth Hacking FC. To illustrate the effectiveness of the approach I recommend, let’s quote some figures from the company I work for, Eloquant: over 20% of the 1,200 people who signed up for our interviews with customer relationship experts this year came from LinkedIn, out of an industry of around 15,000 professionals. Our aim is to unite this community, establish our legitimacy, and then convert the members of this community into visitors of our various events such as webinars or our “All for Customers” trade show in Paris. The omnichannel approach is becoming essential as traditional channels become saturated. The numbers are not adding up: the rate of participation in webinars has fallen from 35% 3-4 years ago to around 25% today, 30% at the most. The rate of viewing replays has also fallen, from 15% to 12%. These figures show that it is no longer viable to rely on a single channel. Omnichannel is of the essence, and face-to-face meetings especially, that are more effective than ever. How important is personalisation in your approach? FC. Personalisation is vital. For birthday wishes, we take a two-step approach: an initial message automated by my assistant, followed by personal interaction on my part. And I send the messages one by one. AI won’t replace humans, but professionals who master AI will outperform those who don’t. Our experience with Smart Tribune illustrates this principle: during a joint event, we decided to pull together and appeal to our respective networks and approach each potential participant individually. Success depended on pre-existing relationships and established personal links. This then led to a white paper written jointly with Apizee and Smart Tribune [note: in French only], based on an OpinionWay survey of 1,000 interviewees. Our partners used AI to kickstart the writing of this project. While AI was impressive at the start, it was quite obvious after a while that all this was more artificial than intelligent: the formatting was bland, transitions were artificial. All that was typical ChatGPT gibberish. We had to substantially correct all these initial sections. AI remains a valuable tool, particularly for copywriting. I use a custom GPT to generate drafts of posts about my events. The result, while not exceptional, provides us with a straw man, which can then be adapted and personalised. How is the digital landscape changing with these new AI practices? FC. There has been a significant drop in SEO traffic on Google these past few months. Well-established blogs have been massively hit by the arrival of AI and the automatic generation of content. As Google is struggling to distinguish authentic content, it then started to favour more specialised and industry-specific sites. I’ve noticed that many content creators and bloggers I know have given up or scaled down their online writing. Personally, while blogging used to be my number one priority, it has now slipped into second place. I now prefer to concentrate on LinkedIn.   The post Ethical growth hacking is not an oxymoron appeared first on Marketing and Innovation.

AI is redefining retail for good, bringing in the kind of automation and professionalism once implemented in the manufacturing industry. In this case, it’s mostly revolving around data-driven marketing decisions and in-store retail media capabilities. As shown by Axians, a VINCI group company, AI isn’t a mere toy for undergraduate students who are failing their tests and need better inspiration. It’s a robust, state of the art high-tech engine for growth and better in-store management. Yet, as often with technology, there are two sides of the same coin. The other one is more ominous, though, depicting a future of retail where layoffs will continue to rise, mostly for those retailers who missed that boat of AI-driven customisation. Here is the account of our discussion with Hugo Rocha Gonçalves, Axians’ head of Smart RetAIl, at Tech for Retail 2024.  AI in retail: shrinking queuing times today, headcount tomorrow Zooming in on AI in retail with Axians’s Hugo Gonçalves at Tech for Retail 2024 You’re in charge of the smart retail solution at Axians. What is it? Hugo Gonçalves. We developed the Smart retAIl concept to address the main challenges that the retail industry is facing today. There is a strong need to better understand in-store consumer behaviour, profile and shopping habits. We provide this knowledge to improve store efficiency, and to enable data-driven decision-making. Can you describe the process of Smart RetAIl? H.G. We are using AI and computer vision to accomplish this.  The first step is to understand how the stores are organised, what the shop floor looks like, and also how we can capture this data anonymously — for obvious GDPR compliance reasons — to fuel a data-driven decision process.  After capturing this anonymised data through computer vision, there are a couple of things we need to understand. Such as footfall, who are the buyers, when they are buying, and their paths through the store. We need to map, with the help of AI, the hot and cold zones within the store. Within these zones, we can understand if people are proper shoppers or if they are merely passers-by, and how much time they spend doing their purchases. In a sense, this is some sort of heat map within the store H.G. This is precisely what it is. And with this heat map, we can also understand what products people are looking at, how much time they spend. With AI we are taking this to a new level. This new level includes product tasting and testing. Two good examples are chocolate tasting, where we need to understand through computer vision when a customer is tasting something, which is very important in chocolate stores, and perfume stores. With this technology we can detect if the customer is testing the perfume and then understand if he or she will buy it or not afterwards. AI in retail : Axians had set up a heat map showing how their system was monitoring footfall in front of their Tech for Retail booth This means you are automating the work of market researchers who used to observe in-store consumer behaviour H.G. Indeed. It used to be very tedious work to have someone watching hours and hours of video, trying to understand customer behaviour, customisation, and buying habits. Now we have AI that can process 24 hours of video, covering all the opening hours of a given store. We can process all this data and obtain valuable insights as well as data enriched by AI and computer vision. So you are capturing a flow of images through in-store cameras, how is it working? H.G. This entire process demonstrates the beauty of machine learning and AI. No need to resort to supplementary intrusive devices in the stores. We are using existing in-store CCTV cameras. We subsequently apply AI image processing, frame by frame, on the existing footage. The data is recognised and categorised by the AI automatically. The resulting data provides a lot of KPIs like passerby/buyer qualification, hot and cold zones identification, as I said already. We’re also interfacing with other information systems such as CRM, ERP, or point of sale systems. Doing so we are able to match our data with the sales data. How do you adjust your setup for sales optimisation vs shoplifting prevention? H.G. Indeed, the technology is also helping us in that direction. All the innovation and sophistication lie in the AI processing the image. With the evolution we’ve experienced in computer vision, we no longer need specific hardware to do this. We simply need AI to help us with good machine learning and AI models to process it. What kind of AI are we talking about here, certainly it’s not ChatGPT! H.G. This system has demanded a great deal of knowledge and experience. We have a large group of data scientists at Axians. It’s also important to mention that this solution originated from an AI program launched by VINCI Group called the Leonard program (editor’s note: named after Leonardo da Vinci). This program focuses on solving real challenges we face as citizens in our daily interactions. It’s aimed at using AI to solve real challenges. One of these challenges involves using human expertise and knowledge in conjunction with AI. Her me we are talking of a different kind of AI (coupled with computer vision), not generative AI.  Hence it’s either machine learning or deep learning. What does the training process involve? H.G. Typically, we have a learning curve for these types of systems. We train the model using what we call manual labelling. Manual labelling helps the model understand what a person is. There are already modules that assist us. We don’t need to start from scratch. We have existing models, open models that identify a human in a shop and their interactions. On top of this, we use not only our retail clients for assistance (they help us with the training of the model), but also to understand and label the data correctly. It’s important to note that ours is not an unsupervised process. Here we are talking of supervised AI image processing. Supervised learning ensures the correct labelling of data and effective leverage of AI capabilities. What’s sort of work was involved prior to launch?  H.G. Beforehand a lot of preparatory work was required. We have extensive experience developing AI solutions, especially in computer vision, data processing, AI processing, and data quality. This represents at least two or three years of intensive work, collaborating, testing and trying to understand how to move forward. Whenever the packaged solution doesn’t suffice, we propose POCs to our clients. Such POCs help us reduce overhead related to testing. For example, we are currently testing queue times AI management. From experience, we’ve found that normally when customers are buying something, they won’t wait more than 10 minutes. If the wait exceeds 10 minutes, they’ll leave the queue and give up on their purchase. We’re addressing issues such as these by providing data driven insights. Can you share a real-life business case with our reader? H.G. We have launched a POC in Italy. We’re assisting a large retail client over there. This retailer had realised it was losing sales and that their conversion rate was decreasing because their staff wasn’t supporting their customers, even though that was part of their onboarding training.  The end gain was significant. They’ve reduced queue time by 50% and increased sales in some stores by 12 to 15% due to this implementation. It was sufficient to break even and they are now challenging us with new use cases, including some very complex AI problems. How long does it take to break even with that kind of solution? H.G. It depends greatly on the size of the stores. It’s not a one-size-fits-all solution, but we can say that recovering the cost of the investment in the platform typically takes between 6 to 12 months.  Any examples from Portugal? H.G. Regarding queuing times, we have another example in Portugal involving high-tech retail solutions. The main issue was the identification of the most profitable areas within the store. When selling technology hardware like smartphones, etc., hot zones are of the utmost importance. They are areas  where consumers spend extra time, allowing retailers to sell media space to vendors. This what is known as in-store retail media. In this particular case in Portugal, we achieved great results with a retailer who started to monetise the hot zones in its stores. This wouldn’t have been possible with our platform. Now they know which areas provide more return on investment and can charge more for product placement in these zones. We’re still in the early stages with this client, a major retailer in Portugal. Already, the return in euros is between four and five figures per store. Can your solution help struggling retailers in the current economic environment? H.G. Absolutely. We’re living in a data-driven world. Decisions should all be made based on data. This platform provides extensive in-store data and enables many well-informed data-driven decisions. In the near future, retailers failing  to consider data-driven marketing and AI will have to layoff staff and make other last minute haphazard decisions. Our solution helps uncover KPIs and metrics that were previously hidden. Through data-driven approaches, we’re confident we can help reduce redundancies and facilitate better data-informed decisions. What will retail look like in five or ten years from now? With all these AI solutions, will it still be a labour-intensive business? H.G. It won’t be. There will be a major reconfiguration of stores. Luxury stores will continue to have staff assisting us with purchases. For everyday retail purchases, there will be a significant reduction in staff.  In the future, retail will no longer be a labour-intensive industry The future of retail will also be about extensive customisation. We’re already experiencing this level of customisation in streaming services that trace our personal and behavioural data very w

Data-Driven AI is the future of customer experience, François Ajenstat told us at a recent interview. François is Chief Product Officer at Amplitude, the company behind a digital analytics platform aimed at helping B2B and B2C businesses build better products, websites and ecommerce experiences through behavioural data. François stressed the significance of data-driven AI within analytics but also delivered a clear warning: Don’t fall in love with what you have built! Focus on delivering second-to-none customer experiences instead. He emphasised that implementing chatbots without purpose isn’t beneficial, noting that too often, in this new world, businesses rush to add chatbots but it doesn’t make “anybody happier. No. People are still frustrated.” Data-Driven AI Is the Future of Customer Experience Data-Driven AI Is the Future of Customer Experience — Image generated with Midjourney and our special personalised mode AI Integration and Implementation in analytics, what does it mean? François Ajenstat. While AI capabilities have existed for years through statistics and machine learning, generative AI has opened new possibilities. We’ve integrated this through “Ask Amplitude,” allowing natural language queries with visual responses. Thus, users can simply ask questions about their most engaged users and receive actionable insights. I could ask the system, “Who are my favourite readers, for instance?” Absolutely. And you’d get the answer in a flash and the system would suggest what actions you should take and how you should engage them. Alternatively, it could help you visualise the journey of those users. This is what you call the 3 key aspects of Data-driven AI Implementation F.A. Indeed, we focus on three different areas with a massive potential impact. Simplification first: removing complexity through natural language interfaces. We’ve had speech-to-text capabilities for years, but users often found this feature intimidating. There used to be a learning curve before you could use it properly. Now it’s a lot easier. You just ask a question in natural language and it brings the result for you automatically. Augmentation is the second area: it’s about enhancing human capabilities rather than replacing them. A great example of that might be if you’re analysing some data and you want to understand the outliers* or what the key drivers are. Help me understand the root cause of this problem. This is where you can unleash AI to really drill into the data on your behalf and come up with insights. So we’ve added those capabilities in our product. We’ve also added what we call a data assistant, which will tell you automatically where there are data quality issues or improvements. Last comes Automation: this is where you find workflows and you ask AI to execute tasks on your behalf. It could be about automatically engaging users. It could be around guiding those users by delivering the right content, images, text, based on given use cases. Enabling 24/7 execution of routine tasks while allowing marketers to focus on strategy. The key thing is to engage the user at every single touch point and use AI to make every interaction a little better so you can drive a better outcome. *Outliers (statistics): a data point on a graph or in a set of results that is very much bigger or smaller than the next nearest data point. The 3 key aspects of data-driven AI are simplification, augmentation and automation — visual produced with Midjourney Do you think that AI is made for beginners or super experts like Steve Yegge? F.A. Every time new technologies emerge, it causes fear, uncertainty, and doubt about the jobs that are going to be eliminated. Think of word processing. In the 50s and 60s, the only people who would type were office secretaries. That was a specialised job. When WordPerfect and Word came out to the market, that job got removed. But at the same time, it empowered millions and millions of other people to be able to perform new tasks by themselves. And that was extremely liberating. It doesn’t eliminate the fact that some people are good writers and some people are not. You still need the core skills to know how to write properly. And I think that in our jobs, whether you’re in marketing, engineering or product management, you still need to grasp the fundamentals to understand what is happening. But you can eliminate some of the more basic work and spend more time on the higher level. Yet, Focusing on the Higher Level Requires Skills F.A. Indeed, it does. Think of these new programming languages where you don’t have to learn all the basic hard-coded engineering. You are therefore facing a higher level of abstraction. The same goes with AI. It is merely providing a higher level of abstraction. It makes it possible for you to focus on building greater software versus knowing all the mechanics below it. Data-driven AI means you should be obsessed with user experience, not with AI — image generated with Midjourney. Will AI become a staple of user experience? F.A. AI will become a core capability in all software, driving faster innovation and creativity. The focus on user experience becomes even more critical as expectations rise. Success depends on delivering value to users, regardless of the interface or platform. User expectations are going to grow. And we will all have to compete more effectively or more aggressively on winning the rights to be able to serve those users. I think that changes the equation a lot. We now have a higher responsibility to deliver better quality experiences. But the core of all these experiences is data. We have to be able to collect more and more data to understand what’s working and what’s not working. Just delivering a chat experience on a website doesn’t mean it’s a good experience. Too often, in this new world, businesses rushed to add chatbots. Is anybody happier? No. People are still frustrated. But the real question now is “how do you continuously use that data to deliver better experiences?” To better understand your funnels and user journeys and drive customer retention. Where is user experience headed in the future? That’s the $300-million question. If your website experience is clearly positioned but you are delivering your chat capability through a third-party interface, how do you actually differentiate? All that matters is how much value you are delivering to your users. Don’t fall in love with what you have built. Fall in love with your customers and this should guide you every single day. Could we imagine, in a not-so-distant future, self-programming software? F.A. Users want software that’s adaptable, continuously monitoring itself to drive the right outcomes. I think one of the keys to achieving that is the ability to express the metrics, the goals that you have. Because the software will never know what ‘improvement’ means. Thus, if you were to say, ‘My goal is to increase signup conversions,’ then the software could look at the data and improve itself, change terms, add new buttons and new capabilities that will drive that outcome for you. I think the world actually is shifting from websites to metrics and outcomes. And that’s how AI can come through. There’s a lot of gibberish that comes out of AI because it doesn’t know your intent. It doesn’t know your domain. But if you’re able to start with the intent, then everything else makes a lot more sense. We have a project in development right now where we analyse all the sessions on a given website. We’ll create screen recordings of everything. And from that, we will be able to infer which industry you’re in, where users are frustrated, how users are navigating your site. From that you can start ask AI to suggest changes for you. The whole online world is going to change, is it not? F.A. We’re at an exciting inflection point, like the PC revolution or mobile transformation. AI is going to be a whole new world, but we’re in the very early days. And now’s the time to start dreaming, trying, experimenting. My advice to everybody is to lean in. Don’t be afraid of it. Be the first ones to try and fail and test and really dream of what’s possible because there are incredible opportunities ahead of us. Those who don’t adapt risk being disrupted by those who do. The post Data-Driven AI Is the Future of Customer Experience appeared first on Marketing and Innovation.

Ever heard of cookie pop-ups? It’s true that it’s hard to escape them. Following the 2011 Cookie Directive, sites have finally complied. But rather than deleting cookies, they have installed cookie pop-ups, which throw annoying messages at you and prevent you from surfing the web. They’re useless, mostly because they don’t really improve data confidentiality. Their main purpose is for sites that track your data for advertising purposes to cover their tracks and pretend they’ve become virtuous. Here’s how to get rid of them. How to get rid of the cookie pop-ups Midjourney has imagined Darth Vader devouring cookie pop-ups for us You’re all familiar with those messages that warn you when you’re visiting a website stating that your data will be used, and that your consent is required to do so. 50 times a day you click, but not to get rid of cookies, but rather the cookie pop-ups. Internet users’ knowledge of cookies Thanks to Statista, we can see that more than half (73%) of internet users in the United States are somewhat or completely unknowledgeable about cookies. Using this knowledge, websites take advantage by simply having a cookie pop-up, forcing users to click through to access the content. Europeans are highly exposed to cookies Despite this low level of awareness among French Internet users, ad blockers are used in significant proportions (25%), and irritation with online advertising is also very much in evidence (42%) What are the countermeasures against cookie pop-ups? So, what is there to do to reduce these repetitive, irritating messages? A content blocker sometimes won’t be enough to protect you from these cookie pop-ups. This list is not exhaustive and may evolve. Don’t hesitate to suggest additional solutions, which we’ll add to our benchmark. Firefox for those who still use it Let’s start with this extension for Firefox. Developed by Alessio Capponi, the No Cookie Wall extension claims just 26 users. Brave, the brave Web 3 browser that takes care of cookie pop-ups for you Brave, one of our favorite browsers, has also taken to blocking cookie pop-ups. Here’s what Brave has to say about it in the release of the latest version of the Web3 browser: “You know those annoying cookie consent notifications that pop up every time you visit a new website?”. Newer versions of Brave can hide them and, if possible, block them completely. Simply update to the latest version of Brave.” If you miss the prompt to block cookie consents the first time, you can visit brave://settings/shields/filters and easily enable/disable the EasyList-Cookie List option. Safari or the hunt for cookie pop-ups Safari (exclusive to Apple products) has an even more radical option: block all cookies. It’s so violent that when we activated it this morning, we lost much of the content of this post, which we had to recreate. Handle with care. Because it also deletes session cookies, which are essential if you want to remain connected to a site. This is my case here on WordPress. I’m there most of the day and I don’t want to log in again 20 times a day. The Safari option to block all cookies and cookie pop-ups… deadly and to be handled with care. Session cookies are not involved in cross-site tracking Edge on the verge of an anti-cookie pop-ups meltdown On Edge (Microsoft): Edge is Microsoft’s new browser, also available on Apple hardware. It’s very fast, extremely well designed, and includes Web3 subtleties such as a Wallet. What’s more, it lets you try out GPT4 coupled with Bing (aka Bing AI. Nice, but…). So here’s the CookieBlock extension, straight from Zurich. CookieBlock is a browser extension that lets you automatically delete cookies that don’t respect your privacy. Using advanced machine-learning technology, it classifies cookies into four distinct categories. These are “necessary”, “functional”, “analytical” and “advertising” cookies, which the user can then authorise or reject individually. Unlike cookie pop-ups, which interrupt your browsing experience, CookieBlock only asks you to define your policy once and guarantees that the types of cookies you reject actually get deleted from your browser. What’s more, CookieBlock works on all the websites you visit, and doesn’t depend on the site publisher’s goodwill. Thank God for that! Cookieblock, the Edge add-on that says goodbye to cookie pop-ups DuckDuckGo: hunting bad ducks DuckDuckGo (the browser): the famous privacy-friendly American search engine is the one we’ve been using on a daily basis for many years. DuckDuckGo’s browser is a good starting point for getting rid of all these little beasts. With DuckDuckGo (duck.com) you have nothing to fear from cookie pop-ups. Data confidentiality is included as standard, as is cookie destruction. DuckDuckGo also provides an extension that exposes and rates the ethics of the website you’re visiting (A+/B/B+, etc.) Shining like Chrome… Chrome: Here I’ll pass, if you use Chrome, no need to pretend to hide cookies, you’re the product. In conclusion This overview of anti-cookie and anti-cookie pop-up devices is not intended to be exhaustive. There are many others. It’s a good starting point, however, for avoiding those unbearable and unnecessary messages. The post Protecting your privacy and avoiding cookie pop-ups appeared first on Marketing and Innovation.

Is GenAI content marketing-friendly? Adobe organised a round-table discussion during their Experience Makers conference in Paris at the end of last year. The debate brought together a few digital experts. During this debate, I mentioned that there were limitations associated with GenAI image production and that they weren’t technical. Others contended that it was just a matter of prompt engineering. In my opinion, proper prompting may be recommended, but the limitations of GenAI image generation tools extend far beyond that. Such is my point, which I substantiate in this piece with insights derived from a two-year practice of such online tools while editing this very website. GenAI and Content Marketing Lessons From Experience This debate on GenAI and content marketing was an opportunity to take hindsight about images and their power to illustrate and differentiate our brands. Here we look at how generative AI was used to illustrate the Visionary Marketing news website. This debate on GenAI and content marketing was an opportunity to take a step back and think about images and how they can illustrate and differentiate our brands. Here we look at how generative AI was used to illustrate the Visionary Marketing news website. This debate was organised by Adobe at the Louis Vuitton Foundation in Paris. The main topic was GenAI and its impact on content marketing. This discussion turned out to be an opportunity for me to take stock of a year’s experience of using generative AI to produce images for Visionary Marketing. GenAI and Content: Excitement and Second Thoughts At first, as we discovered Midjourney and its clones, at the end of 2022 we all were very excited. And boy! Did we have fun producing images for all intents and purposes. Then came a moment when one needed to hold our horses. It was indeed high time to take a step back from it all to ponder over the use of GenAI with regard to content marketing. As I explained during the debate, it reminded me of these HDR filters I discovered when I started using Adobe Lightroom 12 years ago. At first, I resorted to them on almost a daily basis. Five years on, in hindsight, I removed all these HDR pictures. Our round-table on GenAI and content marketing: From left to right: Caroline Mignaux, yours truly, Frederic Cavazza, Adobe’s Lionel Lemoine and Fabrice Frossard. Thus, here are a few thoughts on the use of these tools which, in my view, are more than ever, worth investigating. Yet, one should look at them in the context of the widespread use of GenAI tools by both Web users and the Media. Firstly, what was initially pleasurable, at a time we felt like trailblazers, ends up being repetitive and bland. We come across too many of these pictures in the Media and on the Internet. Some of my readers pointed this out to me. My co-author even said he can’t understand why I don’t make more use of my own photos, whereas I am a photographer. He’s both right and wrong, and I’ll come back to that later. In the meantime, I insist that the featured image of this post is an original (and deliberately cryptic) photo by yours truly. Secondly, these pictures, often produced in haste, end up looking the same. They are also often rather garish, with saturated colours that are very characteristic of virtual images. They’re also rather banal and sometimes vulgar. I realise that this is a personal and biased statement. After all, though, when it comes to images, there is no such thing as objectivity. There’s also a general trend towards ‘heroic fantasy’ images, a genre I have nothing against. Even though it’s not to my liking. Regardless of personal tastes, this does seem to add fuel to the fire of the trivialisation of images. To this one may add sci-fi-like illustrations, which are sometimes quite successful, but also confer a déjà vu aspect to your content. Lastly, a feeling of unease about images that are very realistic but at the same time are not. It’s a phenomenon known in the digital world as the Uncanny Valley. We’ll deal with this topic on this site in more detail at a later date. Using GenAI: Three Main Stages In fact, at Visionary Marketing, we went through several stages. In the beginning, we only used images from my personal stock. All the Visionary Marketing content writers had to go through this limited stock of images. These photos are personal, and therefore unique. Yet a feeling of déjà vu soon also set in. And above all, we were often unable to describe certain concepts using those images. It makes sense since this stock doesn’t include all the possible metaphors one would require. Fishing for the right picture amongst 12,000 of them isn’t always a piece of cake. Not to mention the crafting of the right captions, a real challenge that was! Stage 2 of our own discovery process consisted in adding stock photos to our content. This made it possible for us to bypass the above-mentioned limitation syndrome. However, it also made our illustrations look more commonplace. This could have been damaging in some cases. Fortunately, we were using Jumpstory, an image data bank that stood out from the rest. Thus, we avoided this pitfall to some extent. It was good while it lasted, for Jumpstory went under this year. I wouldn’t be surprised if GenAI killed it there and then.  Jumpstory images, like this one, were sometimes quite good. But you had to look hard to find the right one. Anyway, it sadly went under in 2024. Since the end of 2022, Generative AI From the end of 2022 onwards, this is stage 3, we started making more intensive use of generative AI to produce illustrations for our articles. In all cases, whether it be the first, second or third stage, we’ve come to the same conclusion: using the same image source all the time leads to a feeling of repetition, fatigue and trivialisation. I dote on abstract painting for illustrations and Midjoiurney in personalised mode (–p switch) enables just that. I’ve had a lot of positive feedback after publishing this picture even by people who were blatant AI sceptics. Innovation and creativity with AI are also possible, like it or not. Many artists have discovered that too. At the end of the day, to successfully illustrate your content, you are recommended to opt for a mix of the different techniques. Above all, as I explained during the Adobe debate, you have to be able to master the prompt so as to produce illustrations that are clearly differentiated from what other content publishers usually publish on the Net. As explained with the above example, this has been made easier as of mid 2024 when Midjourney started to implement the personalised mode. The more abstract the prompt, the more eye-catching and the more different the image produced. That’s what makes you stand out from the crowd. This is rather counter-intuitive. Indeed, most self-proclaimed AI pundits on LinkedIn and elsewhere will be adamant that such prompts should be banned. What life has taught me, though, is that when the crowd produces A, producing non-A will make your work — and yourself — more distinctive. Besides, advanced mastery of all available image tools (GenAI, Lightroom Classic, Photoshop, Illustrator, or all of them combined), means that you can retain total control over your pictures. Thus, you should be able to produce less commonplace pictures or illustrations for your content. More than ever, marketing is not about getting things done. It’s about getting things done differently. Whether you resort to GenAI or not, you should always bear that in mind. Last but not least, don’t hesitate to revisit your content to change illustrations that, with hindsight, seem too trivial, too stereotyped or too garish. Unless, of course, you like it that way. The post GENAI and Content Marketing: Learning from experience appeared first on Marketing and Innovation.

The state of influencer marketing in Europe 2024 is a survey conducted by Kolsquare, a leading European influencer marketing agency. It provides a particularly interesting perspective on influencer marketing budgets, how influencer marketing is handled and its future trends. Besides, its comparison of Europe’s main markets for IM is clearly enlightening. It’s one of the first if not the first of its kind and it sheds light on the way that businesses are conducting marketing with Key Opinion Leaders, at least for business to consumers. One of the most striking takeaways from this study is the sheer size of the average European influencer marketing budget which is evaluated at a whacking €3.375 million annually.  European Businesses Spend nearly €3.5m Annually on Influencer Marketing The Kolsquare/NewtonX 2024 European survey shows that Influencer Marketing has clearly become pivotal in the B2C marketing mix. Methodology of the 2024 Influencer Marketing Survey This 2024 European Influencer Marketing (IM) survey was conducted by Kolsquare and NewtonX. It involved 385 decision makers representing medium to large organisations across various sectors (Beauty and fashion, IT, SaaS and Telecommunications, Retail food and beverages, entertainment …). All respondents had more than two years of experience in influencer marketing. The sample is relatively large for that kind of B2B survey with five countries surveyed (France, Germany, Spain, Italy, and the United Kingdom) and approximately 80 respondents in each of these countries. Influencer marketing 2024 survey methodology The European influencer marketing landscape Thanks to this survey, we now have evidence that the influencer market is really significant with €3.375 million spent on influencer marketing by European businesses annually, and Germany topping the list at €5.74 million per annum. Micro influencers (10,000 to 100,000 followers) being the most popular partners for the surveyed European businesses. Respondents’ expectations on growth are very optimistic with 54% of them expecting to increase their influencer marketing budget next year. Unsurprisingly, the influencer marketing landscape has shifted towards three main platforms: Instagram, TikTok, and YouTube. More than ever, influencer marketing is here to stay with 27% of respondents saying that it will become more important in the marketing mix. And even 6% stating that it will become the most important part of the overall marketing spend. UK marketers seem less prone to spend huge chunks of their budgets on influencer marketing with a yearly average of £848,000 (still a whopping €1.02 million!) Brands are also declaring that they will become more selective in the influencers with whom they work (56%). Ethics is topping the list of preoccupations in Italy and France, but less in the UK and not that much at all in Germany. Indeed, Germany is described by Kolsquare as “the big spender”, but not very keen on ethical considerations. Unlike the French and Italians, who said to be prioritising corporate ethics when selecting influencers. This emphasises a significant shift in the market, whereas four or five years ago we were stressing the fact that ethics weren’t really on French influencer marketing managers’ priority list. Influencer marketing landscape Social network usage by marketers and Key Opinion Leaders When it comes to social network usage by influencer marketers, the shift towards Instagram, TikTok and YouTube is significant. However, Facebook has not disappeared from the IM landscape completely, as it is still the platform of choice in the UK. X has slipped down the ladder and further down one can find niche platforms such as Twitch, Pinterest, Snapchat and a flurry of Chinese platforms that are clearly less attractive to European marketers. What is surprising, though is that LinkedIn is definitely not part of this list, meaning that the survey is mostly geared towards Business to Consumer marketing. For all intents and purposes, one should emphasise once more that Business to Business amounts to approximately 80% of the production of wealth worldwide. When it comes to size, One can spot a good balance of macro, mega, micro and nano-influencers in marketers’ choices of partnerships. Whereas patterns are relatively similar across countries, micro influencers definitely top the list in almost all of them. One-Shot Versus Long-term Influencer Marketing Collaborations It seems that in Germany and France businesses prefer to work in the long-term with Key Opinion Leaders. However, the structure is rather similar in all countries with a three-tier pattern: approximately 30% of collaborations with long-term partners, 30% for a mix of new and existing influencers, and another 30% of new kids on the Instagram block. This pattern varies slightly according to countries. Content Forms: How the Brands Collaborate With Opinion Leaders The variety of content types that is offered by influencer marketing is noteworthy, with sponsored posts and influencer events as well as product reviews topping the list. However, there are differences according to countries with sponsored posts not being very popular in France (only 23% of respondents vs. 58% on average across all countries). Approximately one third of businesses are keen on performing co-creation with influencers and even nearly 25% of respondents are conducting product creation with them. In conclusion This study is instrumental in showing how pivotal influencer marketing has become in B2C marketing. Barring a few variations, one can say that IM patterns are relatively similar across the five main European countries surveyed. Spending levels are stellar, with German businesses being on a buying spree. One can only hope that IM will help them fight the current economic slump in Europe’s biggest economy. France and Italy are keen believers in IM too. The United Kingdom and Spain are lagging a bit behind, or can be considered more reasonable, it depends on the point of view. The most important indicator (KPIs) for influencer marketers is not the number of followers but the quality of the engagement. And as it suits B2C, it’s even shifting towards sales and conversions. Last but not least, there are a number of challenges to influencer marketing such as striking the right balance between influencer freedom and brand control. A major issue we have consistently highlighted for the past 20 years we have spent in that domain. It’s a significant pain point in most European countries and especially in France, where brand control is tightening on influencers. Measuring ROI and ROAS (Return on Ad Spend) is on top of Italy’s list of issues related to influencer marketing. Apart from that, authenticity and the quality and tone of voice of influencer content is definitely what entices European brands to work with Key Opinion Leaders. What is also most striking is the significance of ethics according to countries. The results seemed very counter-intuitive to me but reassuring, with Southern countries showing a lot of concern for ethics compared to Northern ones. About KolSquare Kolsquare is Europe’s leading Influencer Marketing platform, a data-driven solution that allows brands to scale their KOL Marketing strategies and implement authentic partnerships with KOLs (Key Opinion Leaders). Kolsquare’s technology enables marketing professionals to easily identify the best Content Creators’ profiles by filtering their content and audience, and to build and manage their campaigns from A to Z, including measuring results and benchmarking performance against competitors. Kolsquare was founded by Quentin Bordage in 2018.  The post Influencer Marketing: Average European Spend at €3.5m Annually appeared first on Marketing and Innovation.

The Cyber threat landscape in Europe is quite worrying. A recent survey by Cloudflare was conducted amongst 4,261 IT executives responsible for cybersecurity in Europe. 24% of the sample is made from small enterprises (150–999 employees), 24% from medium-sized businesses (1,000–2,500 employees) and 52% from large organisations (above 2,500 employees). All major European countries were surveyed by Cloudflare in their study entitled Shielding the future: Europe’s cyber threat landscape. The report paints a rather bleak picture but stresses that solutions exist… as long as leadership teams understand what new Cyber threat countermeasures like Zero Trust are about. All in all, this will require all management teams, not just IT, to better understand the ins and outs of such dangers. European Cyber threat Landscape: a bleak picture but there is still hope European Cyber threat Landscape: Cloudflare paints a very bleak picture but there is still hope The sample of this survey is quite comprehensive given its high profile and B2B orientation. The Sample of the 2024 Cyber threat survey by Cloudflare Some of the takeaways from this report on the European Cyber threat landscape include: – All kinds of businesses are impacted by cyber threats with 72% of respondents reporting at least one incident in the last 24 months, – 84% of respondents reported more incidents compared to past years. With a staggering 43% of those organisations experiencing 10 or more attacks in the past 12 months, – Attackers are resorting to a variety of methods, with phishing and Web attacks on top of the list, – A remarkable low number of respondents (29%) state that they are well prepared for future incidents, therefore leaving 71% out of that picture, – Over half of respondents anticipate that their organisation will dedicate more IT budget to cybersecurity, – There is a growing concern that “adding numerous point solutions is not the answer“. With nearly half of respondents ranking “simplifying and consolidating their cybersecurity stack” as one of their top three priorities, – Moving to zero trust security could help but 86% of respondents reported that their leadership teams do not yet fully understand this model. Let’s face the music, How many IT execs are feeling comfortable with the understanding of how our complex online systems should be protected? Well, not that many. However much I hate the idea, it seems that too much openness of such systems isn’t making our lives easier. It seems that an increasingly dangerous cybersecurity landscape is causing more and more aggravation within organisations. The growing complexity of open networks with access to increasing amounts of money is too big a temptation for most cybercrooks to resist. Besides, the staggering complexity of IT, networking and especially cybersecurity solutions such as zero trust explain why there are so few companies that are ready to implement such solutions. However much sense they may make. However much I hate the idea, it seems that too much openness of such systems isn’t making our lives easier. The post Cyber threat Landscape Europe, 2024 appeared first on Marketing and Innovation.