Data & AI Mastery: The AI Executive Podcast
In a world where data is transforming every aspect of business, staying ahead of the curve is crucial. But how do you separate AI hype from real opportunity? That’s where Data and AI Mastery comes in.
This podcast is your source for cutting-edge insights, practical advice, and inspiring stories from the UK’s leading voices in data and AI. We bring you the knowledge and tools to advance your career and make an impact in your organisation.
Tune in to Data and AI Mastery—where data-driven progress begins.
Meet the host
Dr Raoul-Gabriel Urma
Dr Raoul-Gabriel Urma is an EdTech entrepreneur, author, and international speaker focused on transforming workforce development through data and AI.
As the Founder and Chairman of Cambridge Spark, Raoul leads efforts to upskill employees of top organisations, including M&S and the BBC, with cutting-edge training. He co-invented the patented EDUKATE.AI platform, which personalises learning for data skills.
A member of YPO and affiliated lecturer at Cambridge, Raoul is also pursuing the Owner/President Management Program at Harvard. His best-selling book, Modern Java in Action, has sold over 60,000 copies, reflecting his impact on technology and education.
Show Trailer
Latest Episode
From Data Scientist to the C-Suite: Foundations, ROI, and Leading AI at Scale
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.
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