Cloud Wars Live with Bob Evans

In this episode of Cloud Wars Live, Bob Evans speaks with Nathan Thomas, Senior Vice President of Product Management for Oracle Cloud Infrastructure, about the explosive growth and transformative potential of Oracle’s multi-cloud database strategy. Thomas explains how Oracle is enabling customers to run mission-critical databases across AWS, Microsoft Azure, and Google Cloud while unlocking new AI-driven innovation. Their discussion dives into how multi-cloud is reshaping enterprise mindsets, accelerating cloud migrations, and helping organizations fully leverage their data for next-generation applications and agentic AI. Multi-Cloud Momentum The Big Themes: Multi-Cloud Demand Explodes: Oracle’s multi-cloud database is seeing massive demand, driven by customers wanting to run Oracle workloads in the same cloud environments as their applications. This shift eliminates friction between systems. The surge is amplified by AI, as organizations look to connect their data with services like Gemini, Bedrock, and Copilot. The reported 500%+ growth reflects not just technical appeal but a fundamental change in how enterprises think about infrastructure. AI Is the Growth Catalyst: Artificial intelligence is accelerating multi-cloud adoption at an unprecedented pace. Customers want their data co-located with AI tools and pipelines, enabling faster insights and innovation. Instead of moving data across environments with latency constraints, multi-cloud lets organizations bring AI to their data. This creates a powerful feedback loop where better access drives more experimentation and faster results. New Builders, New Energy: The adoption of multi-cloud is bringing in a new generation of developers and AI-focused professionals. These users are actively engaging with enterprise data to build innovative applications and AI-driven solutions. This marks a shift from traditional, tightly controlled database environments to more dynamic, accessible platforms. Organizations are no longer treating their data as static assets, they’re using it as a foundation for continuous innovation and competitive advantage. The Big Quote: “We hear from customers a lot that they struggle with what I would call the tyranny of choice. There's just way too many options, way too complicated." More from Nathan Thomas and Oracle: Connect with Nathan on LinkedIn or learn more about Oracle and multi-cloud. Visit Cloud Wars for more.

In today’s Cloud Wars Minute, I examine how AI and data access are accelerating unprecedented cooperation among cloud leaders. Highlights 00:03 — It's been two and a half years now since that momentous interview featuring Satya Nadella and Larry Ellison talking about their partnership to do multi-cloud between Oracle and Microsoft. And in some ways, I regard this as the multi-cloud miracle, because we've accepted it. 01:10 — It's opening up more ways in which competing tech vendors are going to work together to drive better benefits, better outcomes for customers. So, I had a very interesting interview with Nathan Thomas, Senior Vice President for Product Marketing at Oracle Cloud Infrastructure, where he heads up the multi-cloud effort. And I wanted to talk to him about the benefits. 02:24 — I want to also go back quickly and touch on what Nadella and Ellison talked about two and a half years ago. One of Ellison's first points, he said, this just makes it easier for customers, and they get the benefits of both Microsoft's top technology and Oracle's top technology optimized to work together. 03:36 — At the time, he said, OpenAI, take it to where the data is. So two and a half years ago, Nadella was very keen on this subject of how this multi-cloud partnership between Oracle and Microsoft would benefit the early days of the AI movement. 04:44 — And when you put it in terms of business outcomes, then these competitive things that are behind the scenes matter less and less. So this is an interesting time. I hope we'll see more of this. Visit Cloud Wars for more.

In today’s Cloud Wars Minute, I discuss the significant leadership changes at Oracle and what they signal for the company’s future. Highlights 00:03 — One of the things that has become clear over the last several months is that there are big changes taking place at the top of Oracle. I wanted to go into that a little bit, particularly how this is all leading up to what is an excellent new adventure for company co-founder and chairman Larry Ellison. 00:21 — I think it's a remarkable time here. Now, clearly, I’m not saying that Larry Ellison is stepping aside. I mean, six months ago, we saw longtime CEO Safra Katz move from CEO. She elected to move to the new position of executive vice chairman. In those six months, we've also seen the ascendancy of new CEOs, Mike Sicilia and Clay Magouyrk. 01:09 — Again, this is not about Larry Ellison leaving. I think the new adventure he has was really brought into clear light on the March 10 fiscal Q3 earnings call for Oracle, when there was no opening statement by Larry Ellison. I mean, that's something he's done for the last 150, 160 earnings calls. 01:50 — Then, in the Q&A session on that March 10 earnings call, there were seven questions asked. None of them was aimed at Larry Ellison. They were all aimed at Magouyrk and Sicilia. After the final question, he added some thoughts to what Mike Sicilia had said. His point there is to say these are the new leaders of Oracle, the people helping now to set the direction, execute it, and make sure we're going in the right way. 02:40 — The new CEOs are doing a great job. In my estimation, the way they handled themselves in the answers on the March 10 earnings call was terrific. They were very, very, very persuasive, impressive, and compelling. So we can say this is the end of an era, but I think another way to look at it is that it's the beginning of a new era for Oracle. 04:05 — New ideas, speed, the ability to do things that customers haven't ever done before — and Sicilia and Magouyrk clearly have won the full confidence of Larry Ellison and Safra Catz, who believe now, as Ellison said on that March 10 earnings call, Oracle's future is bright. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I examine how Health 100 signals a major shift toward AI-powered, patient-centric healthcare ecosystems. Highlights 00:03 —Google Cloud has partnered with CVS Health to launch an AI-driven health data platform called Health 100. The platform unifies patient data from a variety of sources, enabling more streamlined health management. CVS Health, which operates both an insurer and a pharmacy retailer, is embracing the spirit of the AI revolutions. 00:36 — Health 100 will connect benefit managers, pharmacies, healthcare providers, and digital health systems into a single platform, regardless of the companies supplying them. And there's more details coming, but what we know so far is that Health 100 will tap built-in AI and generative AI to act as an always-on personal healthcare partner. 01:00 — It will deliver care options faster, be operated on mobile, and interact visually and through voice interactions. Patient data will be protected through Google Cloud security and compliance infrastructure. Now, this is just the latest in a series of partnerships through which Google Cloud is enabling companies to innovate in the healthcare space. 01:24 — Google Cloud is really standing out as a leader now, I think, in this area, focusing on agentic AI in the healthcare space. Now, while agents have been making significant strides in various business sectors and industries, it's really fascinating for me to see the momentum shifting into healthcare. 02:00 — Now we're talking about agentic workflows for patients driven by their own data. This progress is only possible with stringent governance and compliance, and as Google Cloud describes its infrastructure security as “secure by default,” companies are certainly supporting this new era of healthcare from solid foundations. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Tom Smith is joined by Kieron Allen, an industry analyst and AI observer, who shares insights from the 2026 AI Agent & Copilot Summit NA in San Diego. Together, they unpack major themes from the event, including agent orchestration, workforce reskilling, MCP’s enterprise impact, and the evolving human-AI partnership. Key Takeaways Human + AI Orchestration Is the New Core Skill: Allen underscores that orchestration is not just about technology—it’s about people managing AI systems effectively. Humans have to view agents as part of the workforce. This means employees must develop skills to coordinate, supervise, and optimize AI agents, treating them as collaborators rather than tools. The ability to orchestrate multiple agents will become a defining competency in modern organizations. Reskilling Must Address Culture and Collaboration One of Allen's strongest points is that reskilling goes beyond technical training. “We need to understand the AI… not just the tools, but also the cultural elements.” Organizations must prepare employees to work alongside AI, interpret outputs, and adapt workflows. This includes fostering trust in AI systems, redefining job roles, and building a culture that embraces continuous learning and collaboration with intelligent agents. MCP is Unlocking Massive Enterprise Efficiency: Smith highlights MCP as a breakthrough, describing it as a “USB-type connector” between AI and enterprise systems. With up to “650,000 actions” now automatable in Dynamics 365, MCP dramatically reduces manual effort. This standard simplifies integration across platforms, accelerates deployment, and enables scalable automation—making it a cornerstone for organizations looking to operationalize AI at scale. Customer-Centric AI Learning is Accelerating Adoption: Allen observes that many professionals are attending the conference not just for internal use, but because “they’re attending this conference… for their customers.” This reflects a shift where AI literacy is becoming essential for delivering value externally. Businesses are recognizing that understanding AI enables them to better anticipate client needs, create new offerings, and remain competitive. Visit Cloud Wars for more.

In today’s Cloud Wars Minute, I question whether OpenAI’s $140 billion enterprise revenue target is a realistic strategy or a speculative leap. Highlights 00:03 — It was announced recently, or revealed recently, that OpenAI expects that its revenue will hit about $280 billion by the year 2030, half of that enterprise, half of it consumer. So that would mean that by 2030, OpenAI, according to this CNBC report citing anonymous, confidential sources, will have its enterprise revenue be about $140 billion in five years, or less than five years now. 00:48 — As Larry Ellison said, “The baby could talk.” There has been a huge amount of interest around OpenAI. It has also stirred up considerable head-scratching with its agreements to purchase $300 billion of AI training and inferencing from Oracle, and about the same amount, maybe even a little more, from Microsoft. Now, all of this has people wondering, who is this company? What's it going to do? 01:47 — They said it's confidential, but they've seen information about OpenAI’s plans, so maybe we need to take this with a grain of salt. And I typically regard anonymous sourcing reports with about the same passion and love that I have for skin rashes. But I think because of the implications here for OpenAI and what it might mean, I thought this was at least worth mentioning. 02:26 — But they also said that, seeing that OpenAI has now changed its projections for how much compute or AI infrastructure spending it needs to do, Sam Altman had recently said it's going to be $1.4 trillion. Well now, according to the CNBC report, he's pulled that back to about $600 billion. That's a cut of $800 billion, or about 57% of the projections. 03:36 — So the more compute spending we do, the more revenue OpenAI is able to get—that is her premise. Now, if they are indeed cutting their compute and AI infrastructure spending by $800 billion, how then does that equate to this explosive revenue growth? And was that premise—that compute growth equals revenue growth—not true? 04:29 — Now, what about if key suppliers such as Oracle and Microsoft, perhaps Google Cloud, perhaps AWS, are also in this expansive scheme by OpenAI to reach $140 billion in enterprise revenue in four and a half years? What if they become competitors? How do they feel about continuing to be the suppliers of this engine of revenue growth? 05:26 — I don't mean in raising these questions to diminish the impact or the potential that OpenAI has. I think, like any fast-growing category creator as OpenAI has been, there's no roadmap, nobody's done this before, there's no playbook, and they've got to make this up as they go along. Visit Cloud Wars for more.

Microsoft is redefining enterprise productivity by positioning Copilot, agents, and unified AI platforms as the operational backbone of next-generation “frontier firms.” Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, host Tom Smith speaks with Vaishali Vinay, Data Scientist at Microsoft, and Raghav Bhatta, Data Scientist at Microsoft, about their upcoming masterclass at the 2026 AI Agent & Copilot Summit NA in San Diego. They discuss how AI can serve as a threat research partner for cybersecurity teams, augmenting human expertise in threat hunting and detection engineering while helping organizations proactively defend against increasingly sophisticated cyber attacks. Key Takeaways AI as a Threat Research Partner: Vinay explains that traditional threat hunting and detection engineering have historically been highly manual processes requiring significant time and expertise. AI can now assist by analyzing attacker behavior and identifying detection opportunities faster. As Vinay notes, the goal is to augment our human experts and accelerate this threat research process much faster. Scaling Cyber Defense in an AI-Powered Threat Landscape: Bhatta highlights that as AI adoption grows across industries, the volume of data and potential attack vectors increases rapidly. Organizations must therefore adapt AI for defensive purposes as well. “The amount of data which is produced… is increasing at a nonlinear scale,” Bhatta explains. AI copilots help defenders process this scale by assisting with detection engineering, threat hunting, and proactive defense strategies that protect infrastructure and customers from evolving cyber threats. Capturing and Sharing ‘Tribal Knowledge’ Through AI: Cybersecurity often depends on the deep experience of veteran researchers who understand attacker behavior patterns. Bhatta suggests AI copilots can help scale that expertise across teams. He explains that copilots can serve as a “source of tribal knowledge,” enabling newer analysts and teams to leverage insights that historically lived only in the heads of experienced researchers. This dramatically increases productivity and knowledge transfer within security organizations. AI Attackers vs. AI Defenders: The session also acknowledges that cyber attackers are increasingly leveraging AI themselves. That makes defensive innovation essential. Vinay and Bhatta emphasize the importance of building AI systems that analyze attack techniques and automatically recommend detection rules. This dynamic defense model enables security teams to react faster to emerging threats and reduces the manual workload traditionally required to understand complex attack patterns. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I look at why the AI economy is fueling unprecedented demand for cloud services and pushing the world’s top vendors into hypergrowth again. Highlights 00:03 — Things are off to a hot start here in early 2026 with the growth rates for the world's top cloud and AI vendors within the Cloud Wars Top 10 growing nicely across the board here because of the demand from customers for AI and cloud services. In fact, we're seeing the return of hypergrowth, 40% or higher growth rates. 00:27 — Hadn't seen that for a while, and this installment of the Cloud Wars Growth Chart we've got three vendors in that category: Palantir at 70%, Google Cloud at 48%, Oracle at 44%. Behind this all is massive customer demand for cloud and AI services, data, agents, and insights as companies prepare themselves for the rapidly approaching AI economy. 01:47 — Palantir, as I said, was number one, 70%, just over $1.4 billion in revenue last quarter. Google Cloud: 48% to $17.7 billion. Oracle: 44%, $8.9 billion in cloud revenue in its most recent quarter. Microsoft: 26% growth rate on $51.5 billion — by far the largest cloud and AI services vendor. 02:41 — And then SAP in a tie with Microsoft here for fourth place: 26% growth, $6.6 billion in revenue. Across the board for all of the Top 10 companies, we saw an increase in the growth rate from the last time I did the Cloud Wars Growth Chart, which was in mid-December. 03:47 — Businesses are expressing and showing enormous demand for these AI and cloud services. And I think in that context it's important to remember we're just at the beginning of this. As customers see what can be done with AI and advanced cloud services, there's going to be more demand. 04:19 — Because of the incredible competitive dynamics among the Cloud Wars Top 10 companies, the pace of innovation from the vendors is rising. We can expect continued remarkable demand feeding into the Cloud Wars Top 10 — what may be the greatest growth market the world has ever known. Visit Cloud Wars for more.

Key Takeaways Agent transactions: With models like the Universal Commerce Protocol, Google aims to control global agent transactions, relying on Mastercard’s verifiable financial infrastructure to make it viable. Filling voids: Similar to how MCP secures agent access to internal systems, verifiable intent enables agents to securely transact on behalf of humans by closing three gaps in the purchase flow; it secures transactions by validating agent identity, ensures strict adherence to user instructions, and confirms the transaction occurred. Big picture: Google and Mastercard are racing to lay the foundation for agentic commerce, but if no single standard wins, fragmented protocols could recreate the same consumer confusion seen in past payment wars—all hinging on the assumption that agents will define the future of commerce. Visit Cloud Wars for more.

In today’s Cloud Wars Minute, I explore how Oracle is embedding more than 1,000 AI agents into its applications to transform entire industry ecosystems. Highlights 01:18 — I think what we're seeing now here at the cusp of the agentic AI boom is the opportunity for modern technology to transform not just individual companies but entire industries and ecosystems. Oracle said it's now got more than 1,000 agents embedded within and working inside Oracle's applications. 02:21 — This is a big effort that goes beyond just what a specific company is doing, and to do that in an industry-specific, targeted way, thus slashing the time to value for customers. This is the sort of automation, insight, transparency, and visibility that many businesses are eager to have. 03:01 — CEO Mike Sicilia said, we've got a few hundred agents up and operating. The customers have been very eager to use this. They're not buying the whole “SaaSpocalypse” nonsense, and instead they've been eager to say, we're currently using some Oracle apps and we'd like to use more, especially the ones that have the agents in there driving new capabilities. 04:02 — They're seeing what he called a halo effect from this, allowing customers to take on more aggressive and ambitious transformations. Innovation, growth, and acceleration are the key things that are happening across these industry layers. 04:48 — What used to be the enterprise apps business is now apps plus agents plus AI plus data. And Oracle says it wants to use this combination of agent-powered applications so that it and its customers can be the disruptors rather than becoming the disrupted. Visit Cloud Wars for more.

Key Takeaways Shift in AI focus: As Director of AI at Armanino, Montgomery explains that organizations are shifting from last year’s AI experimentation and demos toward defining real business use cases and operationalizing AI; embedding it into processes, insights, governance, and workforce interactions to transform how the business runs. Session overview: One of her sessions, "From Insight to Intuition: Designing Copilot Experiences that Understand People," will provide “a practical blueprint for designing Copilot and agent experiences that people can trust and use,” addressing the gap between building AI systems and thoughtfully designing how employees interact with them. Learning objectives: Turning on Copilot often leads to early experimentation but a dip in trust as users encounter vague outputs, prompt fatigue, and unclear accountability because the experience wasn’t intentionally designed. Montgomery's masterclass introduces an “agent experience” framework called CARE — context, awareness, relationships, and empathy — to help organizations design AI systems that are trustworthy, accountable, and effective in business workflows. Event relevance: The event, explains Montgomery, comes at “an inflection point with AI adoption across businesses,” bringing together technical and business leaders to help organizations move from exploring AI’s possibilities to deploying it responsibly and at scale across their operations. Visit Cloud Wars for more.

Key Takeaways Smart friction: AI prioritizes speed and efficiency, but in retail experiences where shoppers value engagement, intentional friction can enhance customer satisfaction and ultimately drive better returns, giving rise to the idea of "smart friction." Use case: Trader Joe’s, for example, deliberately avoids self-checkout to create smart friction, using wait time to immerse customers in design, promote product discovery, and foster interactions with staff that enhance the overall brand experience. By preserving the elements that make its brand special rather than blindly automating for speed, the grocery retailer has been able to stay competitive despite having fewer locations than many rivals. Don't over-automate: While many AI solutions will benefit enterprises, organizations should be careful not to automate away the core elements that define and differentiate their brand. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, host of the show, is joined by Andrea Pinillos, Senior Technical Program Manager at Microsoft, to discuss practical strategies for enterprise adoption of AI agents and copilots. Pinillos shares insights from her work leading internal Microsoft tooling and previews her upcoming session at the 2026 AI Agent & Copilot Summit NA. Key Takeaways Democratizing AI with Simple Tools: Pinillos emphasizes that organizations don’t need complex infrastructure to begin using AI agents. By combining tools like Excel and Copilot Studio, teams can quickly prototype useful solutions such as employee directories. Her goal is to lower barriers to adoption so more teams can experiment safely. Governance Must Come First: One of Pinillos’ strongest recommendations is to establish governance before deploying AI agents at scale. Organizations often rush into building tools without clear rules about ownership, permissions, or oversight. According to Pinillos, responsible adoption starts with planning. She stresses the importance of “making sure that your organization is making [this] an important factor." Real-World Demonstrations Accelerate Adoption: Pinillos’ summit session focuses heavily on practical learning through demonstration. Rather than discussing theory, she will show attendees exactly how to connect Copilot Studio to an Excel data source, build actions, and enable conversational interaction with data. She believes hands-on demonstrations help organizations move from curiosity to implementation. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how Microsoft is using Copilot Studio and multi-agent orchestration to dramatically improve customer support performance. Highlights 00:09 — Now, one of the best ways to assess the impact of Microsoft Copilot is to examine case studies of the technology in action. Microsoft has announced details of a recent project delivered through Copilot Studio, aimed at enhancing the customer support experience on microsoft.com, building on the Ask Microsoft web agent created using Microsoft Copilot Studio. 00:51 — This new approach resulted in a 61% reduction in latency and up to 70% fewer human escalations. The Microsoft team tested and refined the original web assistant, getting it live within just a few weeks using Copilot Studio tools. 01:11 — However, it was the facilities multi-agent orchestration feature that truly enhanced this project, enabling the team to connect the main agent to sub-agents with domain-specific knowledge in areas such as Azure or Microsoft 365 . 01:34 — Firstly, Microsoft is presenting a very tangible use case for Copilot Studio here. Secondly, it highlights the speed at which Copilot Studio can be used to rapidly deploy and easily edit agentic workflows. And finally, it serves as a really good advertisement for multi-agent architecture and orchestration, which I believe unlocks the most capable AI performance. Visit Cloud Wars for more.

Key Takeaways Session overview: AI is a transformative technology where security is lagging dangerously behind. Polino's session, "A Guide to Security Roles in AI Transformation (Implementation)," will explore why it's critical for organizations to reassess current roles, controls, and systems and proactively design security strategies specifically for an AI-driven environment. Guardrails: AI systems can be easily manipulated through indirect prompts or parameter framing, making it essential to enforce extremely strict guidelines and access controls to prevent unintended exposure of sensitive data. Exploring security with leaders: Organizations must proactively define security policies and controls for AI now to prevent users from going rogue or turning to shadow IT, because inaction will only amplify risk as sensitive data inevitably leaks into unsecured public AI tools. Event takeaways: Polino notes the importance of events like this because they bridge the knowledge gap between AI leaders and everyday business users by equipping them to understand AI early and effectively transfer that knowledge across their organizations. "AI is coming, whether you want it or not. The goal here is to figure out how to use it appropriately, how to make it as safe as you possibly can, and mitigate those risks inside your organization." Visit Cloud Wars for more.

In this episode of Cloud Wars Live, Bob Evans speaks with Bonnie Tinder, founder and CEO of Raven Intelligence, about the surge of hype, confusion, and opportunity surrounding AI in enterprise technology. As headlines claim AI could replace traditional software and “vibe coding” threatens SaaS vendors, Tinder brings a grounded perspective from years of advising organizations on enterprise systems like Salesforce, Workday, and SAP. Their conversation explores what AI can realistically do today, why enterprise software remains critical, and how companies can move forward without falling for hype. Episode 58: AI Hype vs. Reality The Big Themes: Why “Vibe Coding” Won’t Replace ERP: The idea that AI-powered “vibe coding” could replace enterprise applications is a popular narrative, but both Evans and Tinder challenge its practicality. Even companies developing cutting-edge AI models are still relying on traditional enterprise systems. For example, Tinder notes that AI companies themselves are hiring administrators for established software platforms rather than replacing them. Leadership Must Guide AI Adoption: The discussion also emphasizes that AI adoption cannot be left solely to technology teams. According to Evans, the entire executive leadership team, especially the CEO, needs to be actively involved in defining how AI will shape the organization. AI initiatives affect workflows, job roles, data governance, and competitive strategy. Without clear leadership alignment, different departments may pursue conflicting approaches, slowing progress or introducing risk. Fear and FUD Are Slowing Progress: Ironically, the greatest threat from AI hype may be paralysis. Tinder argues that fear, uncertainty, and doubt in the market are causing many companies to delay decisions altogether. Organizations worry about choosing the wrong tools, implementing technology too early, or missing the next wave of innovation. This hesitation can prevent companies from making meaningful progress. Instead of waiting for perfect clarity, organizations should take practical steps. The Big Quote: “You can vibe code your way around [a] notion or a content system, that's way different though, than having an in-house solution for an enterprise software." More from Bonnie Tinder: Connect with Bonnie on LinkedIn. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explain why Oracle’s massive RPO growth proves demand for AI infrastructure is real, not a bubble. Highlights 00:00 — For the last several weeks, we've all been hearing gloom and doom, there's going to be AI overcapacity for data centers, and then talking about all these things that Oracle can't do. I want to talk about this in the context of Oracle's terrific Q3 numbers that came out earlier this week. I hope what they'll do as a residual effect is shut the pie holes of some of these just lame-brain skeptics . 01:15 — So I hope some of those people either be quiet, get off to the sidelines, or maybe think a little bit more about how the world is changing, and the tech vendors, especially the ones in the Cloud Wars Top 10, have to change to meet these new times. So let me describe some of what's behind that in these big numbers from Oracle. 01:38 — Like I said, there is RPO, remaining performance obligation, up 325%. It added $29 billion of new RPO in the quarter. The cloud business, 44%. It's $8.9 billion, very, very strong there. Inside some of those numbers, its multicloud database up 531%. It's a huge jump. That's where Microsoft, Amazon, and Google Cloud all sell the Oracle database to their customers. 02:22 — So a big, big business there, the AI infrastructure business overall up 243%, and the RPO is now up $553 billion, well over half a trillion dollars of contracted business that Oracle has not yet recognized as revenue. So it shows enormous growth for the future. Yet in spite of all these things, we've heard relentlessly from these Chicken Little types. 03:04 — First, that there's an AI data center buildout. This is all a bubble. It's going to explode. There's all these hundreds of millions of dollars in CapEx chasing a dream that will never happen. We've heard a lot about that Oracle, which earlier this year said it's going to use debt financing to fund its data center expansion. That that's terrible. 04:18 — Oracle's wildly profitable. It's in great shape on this. There are still other cry babies who are running around saying that the new CEOs aren't ready to handle this. They were supremely in charge on this earnings call, very, very clear, concise descriptions of the strategy and what's going forward. 05:02 — Now, looking ahead this fiscal year, which ends May 31, Oracle's projecting total revenue $67 billion. A year out from that, fiscal 27, it's projecting total revenue for the company of $90 billion. So the whole company growing 34%, turbocharged by what it's doing in the cloud and AI. This is an extraordinary time to be alive. Don't listen to the doom and doomsday folks. Visit Cloud Wars for more.

In this episode of the AI Agent & Copilot Podcast, Giuseppe Ianni, host of the show, is joined by Diego Araujo, Founder and Chief AI Architect at Fusion Flow Software. Their conversation explores how enterprises are adopting AI agents and copilots within ERP environments, particularly Microsoft Dynamics 365 Finance & Operations. Key Takeaways Start with a “Winning” Use Case: Successful AI adoption begins with identifying a high-impact, low-effort opportunity that delivers immediate value. Araujo stresses the importance of choosing use cases that are repeatable and measurable. He explains that organizations must deliberately identify early wins to build momentum and credibility across teams. User Adoption Determines Success: Technology alone does not guarantee successful AI implementation — user adoption does. Araujo emphasizes that fear and skepticism often prevent employees from embracing AI tools. He recommends involving subject matter experts and users early in the process so they feel ownership over the solution. Governance and Safety Must Be Built In: Enterprise AI systems require robust governance frameworks to ensure compliance, security, and control. Araujo highlights the importance of planning governance early in the process, particularly when deploying agents inside ERP environments that manage critical business processes. He cautions organizations to build mechanisms that prevent agents from causing unintended outcomes. “You don’t want an agent going rogue,” he explains. Measure Value with Clear Metrics: AI initiatives must demonstrate measurable impact rather than relying on hype or novelty. Araujo stresses that organizations should identify metrics that directly tie AI capabilities to business outcomes. “Coolness is not a factor,” he explains. Instead, companies must define operational indicators such as efficiency gains or cycle time reductions. AI Agents Enable a New Workforce Model: Araujo describes a major shift in how employees interact with technology as AI agents become widely adopted. He suggests that individuals will increasingly act as managers of multiple digital agents that execute tasks autonomously. This mindset shift opens new productivity opportunities for organizations. Visit Cloud Wars for more.

In today’s Cloud Wars Minute, I look at ServiceNow’s new Autonomous Workforce and what it means for the future of the digital workforce. Highlights 00:03 — As companies become more familiar with the scope and capabilities of agentic AI, they're seeking more efficient ways to integrate these features into their workflows. And in line with this trend, ServiceNow has launched the Autonomous Workforce: teams of AI specialists that will enhance teams with domain-specific AI knowledge. 00:29 — So how does the Autonomous Workforce operate in practice? Well, the AI specialists deployed by the system have defined roles and work alongside human team members. ServiceNow explains that this shift represents a move away from AI agents that complete individual tasks to teams of AI specialists that take on specific roles. 00:57 — These specialists execute entire workflows from start to finish autonomously. Teams can onboard pre-skilled AI specialists with just a few clicks. These specialists are familiar with their roles, permissions, and, crucially, the historical enterprise context. Companies can scale the scope of the specialists on demand to match spikes in activity. 01:20 — The first out-of-the-box specialist is theLevel 1 Service Desk AI Specialist which can autonomously diagnose and resolve typical IT support requests like password resets or network troubleshooting. Proof of concept for this new system lies with ServiceNow, where the Autonomous Workforce is already handling over 90% of employee IT requests. 02:01 — What's truly remarkable is the redefinition of the work of the digital workforce. Having a context-aware, independent worker for specific tasks is a really outstanding achievement and development. It embodies the futuristic vision of a robotic worker and, in reality, is somewhat more streamlined than many of the widely dispersed agentic systems that I've come across today. Visit Cloud Wars for more.