At this year’s Big Data LDN, the panel “Governed Data Models: The Secret Sauce AI Can’t Live Without” brought together some of the brightest minds in data and AI: 

• Sarah Levy, Co-Founder & CEO of Euno
• Joe Reis, Bestselling author & speaker, Reis Megacorp
• Shachar Meir, Data Advisor, ex-Meta 
• Guy Fighel, Ex-SVP of Data & AI at New Relic, Partner at Hetz Ventures
• Rob Hulme, Analytics Team Lead at Village Hotels
• Harry Gollop, Host of The Stacked Data Podcast, Cognify Search.

Together, they tackled one of today’s most pressing questions: how can organizations truly achieve self-serve analytics and make AI trustworthy at scale?

As Shachar Meir perfectly put it, “Never in the history of mankind was it so easy to ask the wrong questions and get the wrong answers.”

That single line captured the tension at the heart of modern data work: we have unprecedented power to analyze, automate, and accelerate, but without governance, context, and alignment, AI risks amplifying mistakes instead of insight.

Three key takeaways from the session:

1. Governance is evolving: static data models are giving way to dynamic, context-rich systems powered by metadata and semantic layers.
2. Self-serve is as much a people challenge as a tech one: awareness, trust, and data literacy matter as much as the platform itself.
3. AI needs context to deliver truth: metadata is emerging as the connective tissue between raw data and intelligent, reliable automation.
   
   

Each panelist brought a unique perspective: from Joe’s reflections on data modeling’s constant reinvention, to Guy and Sarah’s insights on agentic systems and metadata activation, to Rob’s reminder that every model must start with business meaning.

If you care about building data systems that truly empower people and AI alike, this conversation is a must-watch.

Watch the full panel here: