Agentic AI, Data Foundations, and the Future of Enterprise AI

Agentic AI, Data Foundations, and the Future of Enterprise AI

From The Ravit Show by Ravit Jain

May 19, 2026 · 13 min

About this episode

The episode discusses the challenges of operationalizing AI due to data quality and accessibility issues.

Spent time at Qlik Connect this week and one thing became very clear to me. Everyone is talking about AI, but very few are talking about what actually makes AI work. I had a great conversation with Sean Stauth and Kyle Jourdan from Qlik, on The Ravit Show and we went beyond the usual AI hype. What stood out to me is that most teams are not failing at AI because of models. They are getting stuck on data. Not because they don’t have data, but because they don’t trust it, can’t access it easily, or simply can’t operationalize it fast enough. That gap between “we have data” and “we can actually use it for AI” is where most projects slow down. We also spoke about the constant tension between speed and foundations. Everyone wants to move fast with GenAI, but if your data layer is weak, you are just scaling confusion. The real challenge is not choosing between speed or building the right foundation. It is figuring out how to do both at the same time. Another point that stayed with me was around agentic AI. Grounding LLMs in enterprise data is no longer optional. It is the difference between something that looks good in a demo and something that actually works in production. And again…

People in this episode

Host: Ravit Jain

Guests: Sean Stauth, Kyle Jourdan

Topics covered

  • AI
  • data quality
  • enterprise AI
  • data governance
  • GenAI
  • data accessibility

Keywords

  • Agentic AI
  • data foundations
  • enterprise AI
  • data trust
  • AI projects
  • GenAI
  • data layer

Mentioned in this episode

Organizations: Qlik

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