Data & AI Mastery

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com On this week's episode of Data & AI Mastery, Luke Pearce, Chief Data and AI Officer at Santander UK, joins Dr. Raoul-Gabriel Urma to discuss what it actually takes to drive meaningful AI adoption inside one of the UK's largest banks. Luke shares how Santander UK moved beyond a governance-heavy data culture to build genuine C-suite and board-level sponsorship for AI. He challenges the conventional cost-saving narrative around AI ROI, making the case for customer and colleague delight as the more powerful North Star. The conversation covers how Santander UK structured its AI rollout using a domain-based approach, why cross-functional teams are critical to success, and how to have productive governance conversations with a board that is both excited and cautious about AI. Luke also offers a genuinely contrarian view on the future of the CDO role and what he would change about the industry if he could. A practical and candid episode for any senior data or AI leader navigating organisational complexity. Follow the podcast on Apple Podcasts, Spotify or YouTube so you never miss an episode. Chapter Markers (00:00) - Introduction and Luke Pearce's Career Journey (04:51) - How Industry Experience Shapes Data Expectations (07:24) - Organisational Structures That Support Data and AI (10:19) - Redefining AI ROI Beyond Cost Reduction (14:13) - Board and C-Suite Expectations: Navigating the Difference (18:25) - Lessons for Organisations Just Starting Their AI Journey (22:29) - Picking the Right Domains and Managing AI Momentum (26:21) - Quickfire Round: Contrarian Views and Personal Insights (30:13) - Episode Wrap-Up and Key Takeaways Useful Links Connect with Luke Pearce on LinkedIn: https://uk.linkedin.com/in/luke-pearce-23121522 Follow Raoul for more AI insights on LinkedIn: https://www.linkedin.com/in/raoulurma/ Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com On this week's episode of Data & AI Mastery, Miryem Salah, Director of Digital, Data and Transformation at VodafoneThree, joins Raoul Gabriel-Urma to share the story behind one of the most ambitious AI strategies in UK telecoms. Miryem breaks down how her team approached building a forward-looking AI strategy from first principles, why most organisations fall into the FOMO trap, and how VodafoneThree is thinking about the balance between humans and AI in a post-merger business. She also shares her thinking on governed agility, the importance of data literacy at every level of leadership, and why getting foundations right matters more than chasing the next shiny tool. The conversation also touches on diversity in data and tech, Miryem's Women in Data network spanning 100,000 employees across VodafoneThree; and her genuine excitement about the rise of physical AI. A frank, experience-led conversation for senior data and AI leaders navigating large-scale transformation. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.  Chapter Markers (00:00) - Introduction and Miryem's role at VodafoneThree (02:00) - Inside the Vodafone and Three UK merger  (06:00) - Misconceptions about data teams and data ownership  (10:00) - Operating model, human versus AI, and the sell-build-run framework  (15:00) - Measuring success in early-stage AI deployment  (19:00) - Risk management and when to put AI in front of customers  (24:00) - Quickfire round: diversity, STEM, music and the magic wand question  (27:00) - Raoul on AI and the future of education  (28:30) - Key takeaways Useful Links Connect with Miryem Salah on LinkedIn: https://uk.linkedin.com/in/miryem-salah-7a3ba633  Follow Raoul for more AI insights on LinkedIn: https://www.linkedin.com/in/raoulurma/ Explore Cambridge Spark’s AI upskilling programmes at https://www.cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to turn strategy into measurable impact: cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma sits down with Indhira Mani, Chief Data Officer at Intact Insurance UK, to explore what it really takes to transform a legacy organisation into a data-driven, AI-enabled business. Indhira shares her journey from embracing intellectual challenges to leading a full-scale data transformation, not by starting with technology, but by starting with people. Together, they unpack how to move data from a back-office function to a strategic lever, how to build cross-functional squads, and why winning hearts and minds is the hardest and most rewarding part of transformation. Listeners will learn why data transformation must begin with culture, trust, and relationships; why giving more data doesn’t always lead to better decisions; and how AI should augment human intelligence, not replace it. This episode is essential listening for CDOs, CIOs, transformation leaders, and executives navigating cultural change in complex, regulated industries. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.  Chapter Markers (02:00) — Indhira’s journey to Chief Data Officer (05:00) — Moving data from back-office to strategic lever (10:00) — The rewards of transformation (16:30) — Making data usable, not perfect (19:00) — Decision paralysis and too much data (23:00) — Raoul’s reflections  Useful Links Connect with Indhira on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to deliver responsible, real-world impact: cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma is joined by Edmund Towers, Head of Advanced Analytics & Data Science Units at the Financial Conduct Authority (FCA), to explore how data science and AI are being used to protect consumers, fight financial crime, and enable safe innovation across financial services. Ed leads advanced analytics and data science across the FCA, working at the intersection of technology, regulation, and public good. From identifying scams and money laundering to shaping the UK’s regulatory approach to AI, his work demonstrates how responsible use of data and AI can deliver real societal impact at scale. Together, Raoul and Edmund unpack how regulators can both enable innovation and protect consumers, why outcomes-based regulation matters, and how initiatives like AI Live Testing are helping firms move from proof-of-concept to safe deployment. This episode is essential listening for data and AI leaders, compliance and risk professionals, policymakers, and executives who want to understand how AI can be used responsibly to deliver trust, safety, and innovation, not just efficiency. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers (01:40) — Edmund Towers’ role at the FCA (04:20) — Why the FCA must both regulate and innovate (08:40) — Introducing the FCA’s AI Live Testing initiative (12:40) — FCA strategic priorities: financial crime, consumers, innovation (16:00) — Synthetic data and collaboration with the Alan Turing Institute (19:20) — Reducing friction in complex financial decisions (22:30) — Quick-fire round: favourite language, subjects, and music (23:30) — Raoul’s reflections on regulation, innovation, and collaboration Useful Links Connect with Edmund on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

👉 Discover how Cambridge Spark helps organisations build the data and AI capabilities leaders need to drive real business impact: cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma is joined by Kevin Cassar, Chief Data & AI Officer at TalkTalk, to explore what it truly takes to lead data and AI transformation from the ground up, and from the boardroom down. Kevin’s journey is a rare one. Starting as a data scientist, completing a Level 7 Data Science & AI apprenticeship, and rising to the C-suite, he brings a uniquely grounded perspective on leadership, ROI, foundations, and people-centred transformation. Together, they unpack how high-performing data teams are built, how AI initiatives win executive buy-in, and why getting the foundations right is the difference between sustainable impact and expensive tech debt. Listeners will learn the three critical skills every Chief Data & AI Officer needs today, what “strong foundations” really mean and why continuous learning and upskilling are non-negotiable in fast-moving AI environments. This episode is packed with practical guidance for CIOs, CDOs, AI leaders, and aspiring executives who want to scale AI responsibly, deliver ROI, and build teams that can keep learning as the business evolves. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (01:40) — Kevin Cassar’s career journey from data scientist to C-suite (04:50) — Getting the foundations right to accelerate later (09:10) — Translating AI work into business value (14:00) — Better customer outcomes and operational efficiency (18:40) — Bringing the business along every sprint (22:20) — Lessons from Kevin’s Level 7 apprenticeship journey (28:40) — Measuring maturity: how to show progress to the CEO (31:40) — Quick-fire round: contrarian views on AI (36:00) — Raoul’s reflections: pitching AI, foundations, and balance Useful Links: Connect with Kevin on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Discover how Cambridge Spark helps organisations build the data and AI capabilities needed to deliver measurable business impact: cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma is joined by Conny Ploth, VP of Global AI Transformation in the financial services sector, to unpack what it really takes to deliver measurable, people-first AI transformation in complex, regulated organisations. Conny brings a unique perspective shaped by a career spanning microfinance, consulting, ESG, and large-scale financial institutions. Her message is clear: if you can’t measure it, don’t start it and AI transformation only succeeds when data, people, and processes move together. Together, they explore how leaders can move beyond AI hype and focus on impact, adoption, and sustainable value creation. Listeners will learn why measurement and baselines are non-negotiable before starting any AI initiative, how to balance quick wins (task automation) with longer-term transformational bets and how legacy organisations can compete with AI-native startups by creating safe spaces for experimentation. This episode is packed with practical guidance for CIOs, transformation leaders, and executives who want AI to deliver real outcomes — not just prototypes. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (01:40) — Conny Ploth’s career journey into AI leadership (06:00) — The three AI value levers: efficiency, growth, experience (10:50) — Governance, guardrails, and balancing access with protection (14:30) — Setting the AI vision and aligning with business strategy (18:40) — Identifying quick wins vs long-term strategic initiatives (24:00) — Running AI as a portfolio of initiatives (28:00) — Upskilling at scale: why experience beats traditional training (33:50) — Quick-fire round: fitness, routines, and personal habits (35:40) — Raoul’s closing reflections: people, process, and purpose Useful Links: Connect with Conny on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Learn how Cambridge Spark helps organisations build the data and AI skills leaders need to stay relevant in a fast-moving world: cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma is joined by Sudhish Mohan, Group CIO & CTO UK and Europe at TransUnion, to explore what it really takes to lead data and AI transformation in a highly regulated, high-impact industry. Sudhish shares his perspective on leading technology and analytics across the credit ecosystem, where decisions affect banks, businesses, and millions of consumers, and why curiosity, judgment, and long-term thinking matter more than ever as AI adoption accelerates. From developer productivity and fraud detection to data governance and cybersecurity, this conversation cuts through the hype to reveal what AI transformation looks like in practice, not in theory. Listeners will learn why curiosity is the most important leadership trait in the age of AI, how TransUnion is approaching AI adoption as a slow, deliberate evolution, not a silver bullet, the difference between more data and better data, and what truly makes a strong data environment Whether you’re a CIO, data leader, or executive navigating AI investment decisions, this episode offers grounded, experience-led insights into building resilient, responsible data and AI capabilities at scale. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.  Chapter Markers: (01:40) — Sudhish Mohan’s role at TransUnion and its real-world impact (06:45) — Why most AI initiatives fail to deliver expected value (10:00) — AI across three buckets: risk, operations, and customer value (12:30) — Using GenAI to improve service desk and operational workflows (17:00) — What makes a great data environment (21:30) — Why curiosity matters more than qualifications (26:30) — Quick-fire round: favourite subject and learning habits (28:00) — Raoul’s reflections: cybersecurity, talent, and hybrid cloud Useful Links: Connect with Sudhish on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Discover how Cambridge Spark helps leaders and teams build the data and AI skills needed to operate in high-stakes, real-world environments: cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma is joined by Andrew Feustel, former NASA astronaut, ISS Commander, and veteran of three space missions. Andrew has spent over two decades at NASA, flying on the Space Shuttle, leading missions aboard the International Space Station, and performing complex spacewalks to repair critical infrastructure like the Hubble Space Telescope. In this conversation, he shares a rare, human perspective on decision-making in the most extreme data environments imaginable: outer space. Together, they explore what space exploration can teach business and technology leaders about trust, automation, AI, and the limits of data-driven systems. Listeners will learn how astronauts rely on data, telemetry, and human judgment during high-risk missions, why data never perfectly matches reality, and why that matters in critical environments and why humans must remain in the loop when decisions carry irreversible consequences This episode offers powerful lessons for leaders navigating AI adoption, risk management, and decision-making, reminding us that technology is only as effective as the humans who design, trust, and use it. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (04:40) — Why data is central to every space mission (09:40) — Trust, automation, and critical systems in spaceflight (11:00) — Why we don’t fully trust autonomous systems (yet) (14:20) — Why AI is essential for space telescopes and discovery (16:40) — What makes NASA exceptional at preparing people (19:10) — How AI is already accelerating space innovation (20:30) — Automated rocket landings and decision systems (23:50) — Quick-fire round: unforgettable space memories (28:00) — Raoul’s reflections: trust, AI, and human-in-the-loop systems Useful Links: Connect with Andrew on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Learn how Cambridge Spark helps organisations build the data and AI skills needed to drive cultural and business transformation: cambridgespark.com In this special episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma is joined by three senior leaders from Capgemini: Claire Williams, Vice President for Analytics & AI in the Retail and CPG sector, leads global data and AI transformation for consumer health organisations.Arlene Carsley, Head of Workforce Transformation, focuses on building the culture, skills, and mindset needed for lasting change.Mansukh Mann, Managing Consultant in Workforce Transformation, works at the intersection of data, AI, and talent strategy to ensure technology and people move in sync. Together, they explore what true data and AI transformation look like in practice and why success depends as much on people and mindset as it does on technology. Listeners will discover why the urgency for AI transformation is being driven from the boardroom down and what that means for leaders, how to balance quick wins with long-term value, how to create momentum without losing strategic focus, why 70% of transformations fail, and how to avoid the common traps of poor sponsorship, misaligned metrics, and siloed thinking. This episode is packed with practical lessons for executives, transformation leaders, and data professionals looking to turn AI ambition into sustainable impact. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (01:38) - What’s Driving the Urgency Behind AI Transformation? (08:49) - FOBO: Fear of Becoming Obsolete (12:05) - Leadership Upskilling with Cambridge Spark (17:12) - Why 70% of Transformations Fail (23:10) - Early Warning Signs Your Transformation Is Failing (25:55) - AI for AI’s Sake: A Recipe for Waste (29:50) - Why Skills, Safety and Experimentation Matter (34:55) - Balancing Quick Wins with Long-Term Goals (41:00) - One Piece of Advice for CEOs (45:40) - Raoul’s Closing Reflections Useful Links: Connect with Claire on LinkedIn Reach out to Arlene on LinkedIn Learn more from Mansukh on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com Visit Capgemini’s website for more information

Learn how Cambridge Spark helps organisations and leaders develop the data and AI skills that drive real transformation: cambridgespark.com Ever wondered how Formula 1 teams make lightning-fast decisions at 200mph? In this episode, host Raoul-Gabriel Urma sits down with Ruth Buscombe, former race strategist for Scuderia Ferrari, Sauber, and Haas F1, to unpack the incredible world of real-time data strategy in one of the most high-pressure environments on Earth. Ruth shares what it's really like making million-dollar calls in milliseconds, how her team processes 1.1 million data points per second from each car, and why the best lessons come from spectacular failures (not champagne-soaked victories).  One of the most fascinating parts of the discussion is when Ruth explains the eternal tension between data and gut feel, and why human intuition still matters even when you have the best models in the world.  Spoiler: your "gut" is really just your brain's LLM of past experience. They also explore how F1 teams decide which sensors and data points actually move the needle when margins come down to 0.012 seconds, and what it's like to make high-stakes pit-stop calls with incomplete information (sound familiar, business leaders?).  Ruth also shares some powerful stories about ‘failing forward’, including why Mercedes boss Toto Wolff says "the day we fail is the day our competitors should fear us most." Plus, they look at how AI is transforming sports broadcasting, with F1 now able to search 75 years of race footage using simple natural-language queries. And of course, they wrap up with a quick-fire round covering everything from Python vs MATLAB to favourite subjects at Cambridge and yes, Taylor Swift workout playlists. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. You can check out Formula 1's official site to learn more about the sport, or head to F1 TV if you want to dive deeper into the data and analysis Ruth works on. Whether you're leading a startup, managing a data team, or just fascinated by how top performers think under pressure, this conversation is packed with insights you can actually use. Chapters 00:00 - Introduction: Learning from F1's best failures 02:00 - Ruth's journey from Cambridge engineering to the F1 pit wall 03:00 - The insane scale of F1 data (1.1M points/second!) 06:00 - How do you decide what data to collect? 09:00 - Three pillars: Performance, competitor analysis & race strategy 13:00 - When should you trust data vs. gut instinct? 17:00 - Managing risk like a portfolio manager 20:00 - Creating a culture that embraces pressure 23:00 - AI transforming F1 broadcasting & fan experience 26:00 - Quick-fire: Python, physics & being a Swiftie 27:00 - Key takeaways for business leaders Links Connect with Ruth on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com Visit Formula 1's official site at formula1.com  Visit F1 TV at f1tv.formula1.com

Learn how Cambridge Spark helps organisations and leaders develop the data and AI skills that drive real transformation: cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma speaks with Ming Tang, Chief Data and Analytics Officer at NHS England. Ming has spent her career leading some of the most ambitious digital and data transformations in the UK public sector. Together, they explore how data and AI are reshaping the future of healthcare, from modernising patient journeys and connecting siloed systems to deploying AI tools that help clinicians and operations teams work smarter. Ming’s insights highlight how the right mindset, structure, and curiosity can unlock meaningful impact at scale. Listeners will also discover how the NHS is building a connected, patient-centric ecosystem through the Federated Data Platform (FDP) and the single patient record initiative and why listening and collaboration, not just technology, are key to solving complex system challenges. Whether you work in healthcare, data science, or digital transformation, this conversation offers powerful lessons in leading with purpose, designing around users, and scaling innovation responsibly. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (03:30) Lessons from leading large-scale transformation (06:00) Why listening and curiosity matter more than technology (11:00) Designing flexible, modular NHS systems for efficiency and collaboration (15:00) The Federated Data Platform: enabling connected, data-driven care (18:00) Real-world AI applications in the NHS: discharge summaries, voice tech & analytics (21:00) Advice for leaders; adopting AI through curiosity and context (25:00) Raoul’s reflections; leading with empathy, curiosity, and user-first thinking Useful Links: Connect with Ming on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Learn more about how CambridgeSpark.com is helping organisations and professionals master Data & AI skills to stay ahead in the digital era. In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma sits down with Dr. Petar Veličković, Senior Staff Research Scientist at Google DeepMind and Affiliate Lecturer at the University of Cambridge. Together they explore how cutting-edge AI research transitions from theory to practice, spanning from breakthroughs in graph neural networks that power Google Maps worldwide, to the use of AI as a discovery partner in mathematics. Petar shares his journey from Serbia to Cambridge to DeepMind, and the pivotal lessons learned at every stage. Listeners will also hear how DeepMind’s graph machine learning models improve global travel-time predictions in Google Maps, how AI can accelerate scientific discovery, including mathematical proofs and what the concept of an “AI scientist” might mean for the future of research. Whether you’re a data scientist, ML engineer, or executive exploring AI strategy, this episode offers a masterclass in applying AI innovation with purpose and impact. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (06:00) - Inside DeepMind; what a Senior Staff Research Scientist does (13:00) - From research to real-world impact: challenges & latency trade-offs (19:00) - AI for mathematics; collaborating with top researchers (25:00) - Defining the “AI scientist” and the future of autonomous research (30:00) - What’s next for AI agents and self-directed systems (31:00) - Quick-fire round; programming languages, school favourites & music (33:00) - Raoul’s takeaways; user focus, AI as a thought partner, safe deployment Useful Links: Connect with Petar on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Learn more about how CambridgeSpark.com is helping organisations and professionals master Data & AI skills to stay ahead in the digital era. In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma, Founder of Cambridge Spark, sits down with Andy MacMillan, CEO at Alteryx, to explore how businesses can get real about data and make AI truly practical. Andy shares how Alteryx helps people who understand data, but aren’t developers, build automations and AI-driven insights using messy, real-world data. He also offers a candid CEO’s perspective on what it really takes to make AI work at scale, from building AI alongside legacy systems, to designing responsible governance, to empowering every employee to use data effectively. Andy also goes on to share how organisations can move fast and deliver value without waiting for the “perfect” infrastructure. He unpacks what agentic AI really means in the enterprise; how to give AI the right context and business logic to make accurate, trustworthy decisions and why hands-on leadership matters.  Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (02:00) – What is Alteryx and how it empowers non-developers (08:00) – How CEOs can responsibly bring AI into the business (15:00) – AI’s role in automation and pattern recognition (24:00) – Responsible AI at Alteryx: Data clearinghouse model (27:00) – Quick-fire round: Contrarian views, leadership, and learning (33:00) – Raoul’s closing reflections and key takeaways Useful Links: Connect with Andy on LinkedIn Visit the Alteryx Website Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Visit cambridgespark.com to explore how we help organisations upskill their workforce in Data & AI. In this episode of Data & AI Mastery, Dr. Raoul-Gabriel Urma speaks with Aidan Innes, Head of Data Standards at Nuffield Health, the UK’s largest healthcare charity. Aidan shares his unique journey from sports science into data leadership, revealing how he built a strategy that connects patient outcomes, data literacy, and advanced analytics to drive both social and financial impact. Elsewhere in the episode the pair discuss building outcome frameworks that scale across a complex healthcare organisation and how Nuffield Health is leveraging data apprenticeships to boost literacy, save millions, and empower staff. Whether you’re a healthcare professional, a data leader, or simply someone passionate about how data drives impact, this episode is packed with insights and actionable takeaways. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (05:00) – COVID-19 rehabilitation programme and measuring outcomes (08:00) – Scaling outcome frameworks across the organisation (12:00) – Technology, governance, and people in data strategy (16:00) – Measuring ROI and success stories in procurement (18:00) – Advanced analytics and award-winning projects (22:00) – Quick-fire round: contrarian views, learning habits, and personal insights (24:00) – Aidan’s vision for the future of data in healthcare (26:00) – Closing reflections and takeaways Useful Links: Connect with Aidan on LinkedIn Visit the Nuffield Health Website Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Start your data & AI transformation journey with Cambridge Spark. What does it take to prepare students—and their teachers—for a future shaped by AI? In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma sits down with Prof. Sue Sentance, Director of the Raspberry Pi Computing Education Research Centre at the University of Cambridge, to explore the evolving landscape of computing education.  From the importance of teaching AI literacy and programming skills, to the challenges of teacher development and interdisciplinary learning, Sue offers research-backed insights into what inclusive, future-ready education should look like.  They discuss the role of pedagogy like PRIMM, frameworks such as SEAME, and why critical thinking—not just technical know-how—is essential for navigating today’s digital world. Whether you're an educator, policymaker, or AI enthusiast, this conversation will leave you rethinking how we equip the next generation with the skills to engage with, critique, and shape AI technologies. Chapter Markers: (00:00) Start Your Journey into AI Mastery Kick off with Dr. Raoul-Gabriel Urma as he sets the stage for this episode's deep dive into computing education and AI literacy. (01:20) Discover Prof. Sue Sentance’s Path to Shaping Computing Education Explore Sue’s unique journey from AI PhD to classroom teacher to academic leader in computing pedagogy. (03:29) Unpack the Latest Research in AI and Programming Education Learn about Sue’s current work, including AI education, debugging, and longitudinal studies in physical computing. (04:43) Master the Skills You Need in the Age of AI Find out what essential skills students need today to thrive in an AI-driven world—and why confidence and critical thinking are key. (08:51) Learn Why We Must Teach AI—and How to Do It Effectively Sue explains why understanding AI isn't optional and offers insights on how we can teach it meaningfully in schools. (11:59) Break Down AI Literacy with Real-World Frameworks Get to grips with leading AI literacy models from UNESCO, OECD, and the EU—and their implications for education. (15:01) Get Actionable Advice for Parents Navigating AI and Tech Sue shares how parents can support their children in learning about AI—even without technical expertise. (17:23) Explore the Line Between Teaching with AI and Teaching About It Understand the difference and how educators can responsibly integrate AI tools into teaching practices. (21:26) Debate the Future: Should We Still Teach Programming? Sue tackles the hot topic of whether coding still matters in an age of generative AI—and what we risk if we stop. (24:08) Hear Personal Insights in a Rapid-Fire Q&A Find out Sue’s favourite programming language, subjects at school, and the music that fuels her work. (28:23) Wrap Up with Final Thoughts on Empowering Learners with AI Raoul reflects on key themes, from coding's long-term value to the role of education in fostering AI literacy. Useful Links: Enjoying the Show? If you enjoyed this conversation, help us spread the word: Rate & Review on Apple PodcastsVisit Cambridge Spark to explore programmes that future-proof your data & AI skillsConnect with Dr. Raoul-Gabriel Urma on LinkedInConnect with Prof. Sue Sentance on LinkedInExplore Cambridge Spark’s AI upskilling programs at cambridgespark.com

Start your data & AI transformation journey with Cambridge Spark. In this episode of Data & AI Mastery, Dr. Raoul-Gabriel Urma speaks with Matthew Cloke, Chief Technology Officer at Endava, about how one of the world’s leading technology companies is embracing AI at scale. Matt shares how Endava created an AI committee to set governance and strategy, built cross-functional champions networks and celebrated AI heroes to drive adoption, and invested in ChatGPT Enterprise across 8,000 employees, achieving 85–90% daily usage. The pair also dive into the business case for AI and how to secure executive buy-in and why creating "wake-up moments" for executives is critical. Whether you’re a senior leader shaping AI strategy or a professional curious about scaling adoption, this conversation is packed with actionable insights. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.  Chapter Markers: (03:45) Who owns the AI agenda? Inside Endava’s AI committee (10:30) The Champions Network & AI Heroes (15:20) Making the business case for ChatGPT Enterprise (25:30) “Wake up, crawl, walk, run”: driving executive aha moments (29:30) Balancing wait-and-see vs. first-mover advantage (32:40) Quickfire round: contrarian views, environment, favourite language & more (38:40) Closing reflections & key takeaways Useful Links: Connect with Matthew on LinkedIn Visit the Endava Website Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programs at cambridgespark.com

Learn more about Cambridge Spark and how we’re helping organisations upskill their workforce in Data & AI: https://cambridgespark.com In this episode of Data & AI Mastery, Dr. Raoul-Gabriel Urma sits down with Tamar Yehoshua, Advisor and former President of Product & Technology at Glean, and former Chief Product Officer at Slack and VP at Google. Tamar brings decades of experience leading product and engineering teams at the most influential tech companies. Throughout this episode you will learn what AI literacy looks like in the boardroom today and why imagination, not just infrastructure, is the biggest barrier to AI transformation. You will also hear Tamar give us her take on the evolving role of AI agents in reshaping work across engineering, sales, and product and how the next generation of leaders can bridge the gap between incremental improvement and radical reimagination. You’ll also hear insights on how top companies are defining their AI metrics, the role of boards in demanding ROI from AI investments, and why the most successful leaders are those who remain authentic, transparent, and consistent. If you’re navigating AI transformation or leading teams through change, this is a conversation you won’t want to miss. Chapter Markers: (03:45) Tamar's leadership principles (11:44) What metrics matter for AI? (16:28) Use cases and real-world AI agent examples (19:06) What is Glean and how does it work? (25:52) From incremental improvement to reimagination (28:54) Quickfire round: Lisp, math, musicals (29:36) Closing reflections & key takeaways Useful Links: Connect with Tamar on LinkedIn Visit the Glean Website Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programs at cambridgespark.com

Learn how Cambridge Spark can help your business transform with data and AI: https://cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma sits down with Daniel Hulme, Chief AI Officer at WPP, to explore a bold rethinking of artificial intelligence—beyond automation and into adaptive, evolving systems. Daniel shares how marketing is being reengineered through AI—dynamic segmentation, synthetic audiences, brand-safe content generation, and more—and how businesses must focus on frictions rather than blindly chasing trends. Drawing on decades of experience, he also reveals a powerful framework for AI defensibility built on data, talent, and leadership. This is a must-listen for executives, AI practitioners, and innovators eager to move past hype and into action. 🎧 Enjoyed this episode? Subscribe and follow to catch more discussions with data & AI leaders who are transforming their industries. Chapter Markers: (05:50) The case for goal-directed adaptive systems (08:05) Why businesses chase tech hype instead of solving problems (12:34) Case study: Using AI to augment creativity at scale (15:07) Micro-moments & the future of personalised, timely marketing (17:00) Real-world transformation challenges (and how to overcome them) (19:05) What gives AI efforts defensibility in business (21:39) Biggest misconceptions business leaders have about AI (24:46) Daniel on staying ahead: predictions, neuromorphic AI, philosophy Useful Links: Connect with Daniel Hulme on LinkedIn Visit the WPP Website Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programs at cambridgespark.com

Learn how Cambridge Spark can help your business transform with data and AI: https://cambridgespark.com In this episode of Data & AI Mastery, Dr. Raoul-Gabriel Urma is joined by James Garner, Head of AI & Data at Gleeds, a global construction consultancy. Together they explore how a traditionally conservative industry is embracing data and AI to drive innovation, improve forecasting, and revolutionise operations. James shares his remarkable journey from chartered quantity surveyor to leading Gleeds' AI and data initiatives. They discuss why domain expertise combined with data science is the new superpower — and why finding these "translators" is so hard. They also cover the importance of hackathons, experimentation, and failing fast to discover valuable AI use cases in construction. And finally they discuss why data quality matters — but isn't the blocker people think it is anymore — and why culture and continuous upskilling are the real keys to AI adoption. Whether you’re in construction, infrastructure, energy, or just keen to see how AI is reshaping even the most traditional sectors, this conversation is packed with practical insights and future-facing perspectives. 🎧 Enjoyed this episode? Subscribe and follow to catch more discussions with data & AI leaders who are transforming their industries. Chapter Markers: (07:10) Data quality, domain expertise, and building that first model (10:22) Taking prototypes to production (11:28) GPT chatbots, LLMs, and the assist tool for industry knowledge (13:48) Why hackathons and safe sandboxing accelerate innovation (16:47) The near future: AI agents, robotics, and blockchain impact (21:30) Worries about industry readiness and losing control to big tech (22:57) Quickfire Round: contrarian views, magic wand problems & learning mindset Useful Links: Connect with James Garner on LinkedIn Visit the Gleeds Website Find out more about Project Flux here Subscribe to the Project Flux Newsletter & Podcast here  Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programs at cambridgespark.com

Transform your workforce with cutting-edge data & AI skills — visit cambridgespark.com to get started today. In this episode of Data & AI Mastery, Dr. Raoul-Gabriel Urma sits down with Jeff Boudier, who leads Product and Growth at Hugging Face, the world’s leading open platform for AI builders. Throughout the episode, the pair explore how enterprises are turning to smaller, specialised open models to solve real business problems; the importance of maintaining control over your data; and how Hugging Face is helping enterprises bring AI safely into production. Whether you’re a CTO navigating how to deploy AI at scale or an engineer eager to sharpen your edge, this episode delivers powerful takeaways on using data & AI strategically — not just for experimentation, but for driving real ROI. Subscribe to Data & AI Mastery and never miss insights from global leaders pushing the boundaries of what’s possible with data. Chapter Markers: (05:50) Real-world ROI: Financial services & patent tech using smaller open models (08:50) When to adopt specialised vs. large models (10:50) The AI adoption curve & why general models aren’t one-size-fits-all (12:30) Protecting your data: governance, builder culture, and avoiding lock-in (14:30) How Hugging Face keeps up with the latest developments in AI (17:50) Supporting enterprises: from rogue IT to secure, compliant AI (21:30) Security, safe tensors & scanning models for vulnerabilities (24:40) Quick-fire round: Jeff’s favourite programming language, subjects & music genre Useful Links: Connect with Jeff Boudier on LinkedIn Visit the Hugging Face Website Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programs at cambridgespark.com