In this opening keynote, we’ll discuss organisations seeing the greatest returns from AI aren’t necessarily those with the most advanced models, but those that have engineered the infrastructure, governance, and context required to make AI trustworthy, scalable, and actionable.

Drawing on lessons learned from working with some of the world’s largest enterprises, this session examines the critical barriers preventing AI from moving beyond pilots and proofs of concept, including fragmented data estates, inconsistent business definitions, rising operational costs, and a lack of trust in AI-generated outputs.

Key focus areas
• Why AI success is fundamentally a data and engineering challenge, not just a model challenge.
• The hidden costs and risks preventing enterprises from realising AI value at scale.
• How leading organisations are creating a trusted foundation for enterprise-wide AI adoption.
• The role of governance, context, and interoperability in building trustworthy AI systems.
• What it takes to move from AI-powered recommendations to AI-driven action.

Justin Borgman, CEO, Starburst

Harleen Thethy, VP of Data & Analytics, Barclays
Sarah Emerson, Group Director of Insight & Business Partnering, Howden
Kyle Winterbottom, CEO & Founder, Orbition Group