Executive Summit

Gartner characterizes the average tenure of a Chief Data and Analytics Officer as "relatively short" - and that's putting it mildly. Most studies show CDAOs keep their job for one and a half to two and a half years. Whether it's expectations of an immediate transformation, a lack of resources or cultural challenges — how can you overcome these early obstacles to firmly establish yourself within your organization?

Join this keynote presentation focused on:

• Balancing the drive for impact with understanding your organization's appetite for change
• Building momentum by collaborating with the right people to champion transformation
• Strategically choosing which challenges to tackle first and which to postpone for lasting success

CDAOs are under pressure to move AI from pilots to measurable production impact — without increasing risk, cost, or complexity. This session pinpoints five critical shifts to help you reach that goal and connects them directly to your 2026 CDAO Gartner survey priorities.

Join this session presented by Rocket Software to learn more about:

• Treating production AI as a data management challenge
• Establishing a governed knowledge layer with runtime sovereignty
• Delivering “data as a product” for agentic driven outcomes

As analytics and AI adoption accelerates, CDAOs are shifting from reactive data quality to proactive, end-to-end visibility across the data lifecycle. By embedding governance and automation, organizations can scale reliable, decision-ready data products that deliver measurable business value.

Join this session to:

• Build trusted, enterprise-scale data workflows
• Enable proactive visibility for scalable data products
• Automate data reliability for analytics and AI success

AI is reshaping where data needs to live and how quickly insights must be delivered. Many CDAOs are finding that traditional, cloud centric architectures can’t keep pace — especially as increased workloads drive new cost, locality, and sovereignty pressures. Modernization now requires rethinking where data sits, not just how it moves.

Join this session to discuss:

• How data locality accelerates delivery and operational efficiency
• When alternative placements outperform single cloud strategies
• A strategic model for reducing technical debt and unlocking enterprise-wide value

Organizations winning with AI aren't just moving fast — they're building the data foundation that keeps AI trustworthy at scale. Yet most enterprises discover too late that operationalizing AI exposes a critical gap: the lack of observability between data pipelines, model inputs and agent outputs.

Join this session to discuss:

• Closing feedback loops between data and AI
• Moving beyond governance
• Balancing cost, latency and scalability

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.

Let's take it back to the basics — ensuring that data is accessible, reliable and truly serves business needs. This foundation opens the door to everything else and is key for successful CDAOs.

This session will explore:

• Aligning data initiatives with your organization's core goals and priorities
• Anchoring stakeholder discussions in real business use cases to ensure relevance and buy-in
• Prioritizing strong foundational data management and defining what "good enough" looks like for your business

The greatest risk in AI isn’t building the wrong solution; it’s solving the wrong problem. Real success comes from identifying opportunities that deliver measurable value by directly connecting AI initiatives to revenue growth, margin improvement, increased speed, or risk reduction. AI is an enabler of strategy, not the strategy itself.

Join this session to discuss:

• Identifying high-impact AI use cases that matter most to the business
• Applying product management fundamentals to AI initiatives to drive adoption and results
• Cultivating the culture for lasting AI success

Open Data Infrastructure is essential for organizations in the AI era, helping leaders scale analytics and AI while maintaining control. CDAOs must balance innovation, flexibility and cost as data platforms expand.
Join this boardroom to discuss:

• Designing interoperable architectures to avoid lock-in
• Applying openness to semantics, metadata and governance
• Enabling AI and operations with flexibility and cost transparency

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