Executive Summit

Many organizations invest in data foundations but are challenged to turn them into governed analytics and AI systems that impact the P&L. Data architecture, technology stack choices and data governance enable scalable analytics and AI that deliver measurable business outcomes. Data readiness and key decisions are critical to maximizing value—both today and as agentic AI reshapes possibilities.

Join this session to explore:

• Evolving approaches to data and governance—structured, unstructured and beyond
• Driving data and analytics modernization—business and technology alignment for results
• Emerging governance challenges—navigating AI’s transition from hype to impact

Many organizations struggle with the high failure rates of enterprise AI projects due to challenges with data quality, transparency and context. Establishing a connected, explainable semantic layer can help make data more AI-ready and improve outcomes. Leveraging advanced tools and frameworks enables more accurate, governable and scalable AI solutions across the enterprise.

 Join this session to explore:

• Improving AI transparency and reliability with a semantic layer
• Boosting AI accuracy through advanced frameworks
• Accelerating deployment and governance with connected data

As AI transforms workflows and accelerates productivity, the skillsets required are rapidly evolving. Organizations must reconsider how they identify, develop and leverage talent in this shifting landscape.

Join this fireside chat with Jena Zangs, Chief Data & AI Officer, University of St. Thomas, and Dr. Manjeet Rege, Director, Center for Applied AI, to:

• Define what “AI-ready” talent looks like in practice
• Explore strategies to unlock professionals' potential
• Discuss how higher education and corporations can strengthen the AI talent pipeline

Connect with like-minded peers in a one-on-one setting through Peer-to-Peer Meetings. You will be matched with peers in your community based on your shared interests and priorities.

AI agents are accelerating decision-making across the enterprise—but many leaders find that even with mature data foundations, organizations still struggle to deploy and scale agents with confidence. The emerging challenge isn’t preparing data alone, but ensuring agents can interpret it with the right context and clarity to make trusted decisions.

Join this session to discuss:

• The “decision trust gap” limiting AI agent performance
• How context, meaning, and governance shape reliable agent actions
• A practical model for assessing agent readiness for auditable outcomes

Agentic AI is transforming business, but CDAOs can only scale AI agents as quickly as they can provide trusted, real-time context. Context intelligence is essential, combining data and business meaning for confident scaling.

Join this roundtable to discuss:

• What are the core data platform capabilities required to serve as a system of context
• How should you structure your AI strategy to balance innovation speed with accountability and measurable outcomes
• Which key metrics should you track to assess data readiness for AI