Ulterior.live
Many organisations have moved beyond agentic AI experimentation, but turning promising pilots into trusted, enterprise-scale capabilities remains a significant challenge. 

The constraint is rarely the model - it’s the data underneath it: fragmented, inconsistently governed, and often stale by the time an autonomous agent needs to act on it. As AI shifts from generating answers to taking action, trust, governance and business context become the deciding factors in whether it scales or stalls, and in whether it delivers measurable business outcomes.

This closed-door executive roundtable brings together senior data, technology and AI leaders to explore what it actually takes to ground autonomous agents in live, reliable enterprise data and obtain outcomes the business wants. The discussion will focus on sharing practical lessons on architecture, governance, cost and performance, and organisational readiness. We’ll explore what separates initiatives that scale from those that stay stuck.

Discussion

Topics

If your AI agents are only as good as the context they can see, what's actually stopping them from getting trusted, business-ready context from your data today?

Is data quality and access still the biggest constraint on scaling agentic AI in your organisation, or are governance, performance and cost (including token consumption) now just as limiting?

For those operating across multiple EMEA jurisdictions, is data sovereignty a blocker you've solved, or one you're avoiding by scoping pilots narrowly?

What guardrails and governance would have to be in place for your board to trust an autonomous agent's decision the way they trust a human's?

Over the next 12 months, where should you invest first to deliver business outcomes from agentic AI: data foundations, AI capabilities, governance or skills?

SUBJECT MATTER EXPERT

Kijoon Lee

Speaker 1

VP, Strategic Alliances at Denodo

Denodo

Kijoon Lee leads Denodo's global strategic alliance with AWS, driving the joint go-to-market and technical roadmap behind integrations such as Amazon Bedrock AgentCore, SageMaker, and Amazon Quick. He works at the intersection of Denodo's Data AI Data Layer and AWS's AI infrastructure, helping joint customers put governed, real-time enterprise data behind their AI agents.

SUBJECT MATTER EXPERT

Joel Farvault

Speaker 1

Principal Specialist Solution Architect GenAI & AI/ML for Automotive & Manufacturing at AWS

AWS

Joel Farvault is Principal Specialist SA, Analytics at AWS. He previously led AXA's Augmented Claims department, applying AI and ML to fraud analytics and claims automation, and served as Chief Data Officer for AXA International & New Markets and Head of Regional Architecture, Data and Innovation. With nearly two decades in data strategy and architecture spanning insurance and banking, he holds a Master's in Computer Science from CNAM in Paris and is fluent in French, English, and Italian.

ABOUT

Denodo

Denodo is a leader in data management. The award-winning Denodo Platform is the leading logical data management platform for transforming data into trustworthy insights and outcomes for all data-related initiatives across the enterprise, including AI and self-service. Denodo's customers in all industries all over the world have delivered trusted AI-ready and business-ready data in a third of the time and with 10x better performance than with data lakehouses and other mainstream data platforms alone.