Welcome to another episode of Data Debrief, the companion show to Driven By Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom sit down to unpack Tuesday’s conversation, share what’s been on their minds, and explore what’s really happening across the data and AI landscape.

Fresh off Kyle’s return from holiday, the pair dive into Tuesday’s episode with Daragh Kelly, Chief Data Officer at The Economist, unpacking the ideas that stood out most, and a few that challenge the dominant narratives in the market right now.

They cover:

Why the concept of “Trad AI” (traditional machine learning and data science) is a useful lens, and how the market is blurring the lines between legacy AI and the new wave of generative and agentic capabilities
The ongoing hype cycle in AI, why it’s nothing new, and how organisations risk getting distracted by buzzwords rather than focusing on real outcomes
The growing gap between building AI solutions and making them scalable, reusable, and commercially viable
The importance of defining what “AI” actually means inside your organisation, and why vague language is creating confusion at the board level
The tension between speed and direction, and why moving fast means nothing if you’re not solving problems that actually matter
Whether operating models really need to change for AI, and why Dara’s perspective challenges the prevailing narrative
The shift from analysts as insight generators to “toolmakers”, and what that means for the future of data and analytics roles
The rise of self-serve capability across organisations, and the risks of uncontrolled experimentation without governance
The ongoing power struggle between CDOs, CIOs, and CTOs over AI ownership, and why the answer is far from settled
The role of optics, titles, and external brand in shaping career progression for data leaders in an AI-first market

Plus, in this week’s Thoughts of the Week, Kyle challenges the long-standing narrative around “having a seat at the table,” arguing that it’s often used as an excuse for not delivering value, and that true impact comes from driving outcomes, regardless of reporting lines. Catherine reflects on the role of diversity, equity, and inclusion in the data community, why the conversation is still far from where it should be, and the responsibility leaders have to actively shape a more inclusive industry.

Like and subscribe wherever you listen, and if you’ve got a question or topic you’d like the team to cover, email community@orbitiongroup.com

Data Debrief: Trad AI, Gen AI, and the Fight for Relevance