AI agents are becoming a critical AI trend as they enable levels of business adaptability, flexibility and agility that can’t be achieved with traditional AI systems trained for a specific task. Their flexibility is valuable in unpredictable operating environments and real-time monitoring and control aren’t practical. Autonomous behaviors have significant societal, legal and ethical implications, but are the answer to the increasing complexity paralyzing our enterprise systems.

Join an interactive executive discussion on emerging trends from the 2026 CDAO Agenda Survey, highlighting cost optimization for D&A, scalable design patterns and the use of AI to improve D&A operations. Discover how these insights can drive efficiency and innovation across your organization.

Data lakehouses continue to be hyped, but do they replace or complement data lakes and data warehouses? Where do we stand from an architectural perspective? What is hype, and what is real? What should be expected in the coming years?

To position their teams as a must-have discipline that can fulfill cross-functional use cases, D&A leaders must optimize their organizational model. The optimal model balances enterprisewide capabilities focused on enablement with decentralized needs focused on outcomes. Discover the design principles that underpin the ideal model and learn how to strike a balance between centralized consistency and decentralized agility.

This session will provide a blueprint for the comprehensive data, analytics, and AI capabilities and services that leaders need to build to enable their organization's AI ambition. It will explore the implications of your AI ambition archetype on your buying, deployment, and organization strategies.

This session will explore the challenges faced by data management leaders and offer actionable recommendations to address them. By understanding and overcoming these obstacles, leaders can optimize their data management strategies and drive more informed decision making.

This workshop will cover the end-to-end process of managing a data product, from ideation to launch. It will include product roadmap development, stakeholder management and go-to-market stra tegies.

Organizations struggle to scale AI governance, mitigate risk, and effect compliance while delivering value in AI deployments. AI governance programs only check the box if they are not adaptive and embedded into the fabric of the AI lifecycle. In this session, you will learn how to define your role in AI governance, assess what technology capabilities are required to govern AI at scale, and make an investment decision in an AI Governance Platform or other technology tool.

This session covers the use and output of Gartner’s AI-Ready Data Toolkit, which includes practices for both structured and unstructured data. The process develops metrics that “stack” as you progress from POCs to multicontext data use, operationalization and production support. The session also explains how to customize the toolkit with your own thresholds and readiness analysis.

AI is accelerating new possibilities for data and analytics everywhere. Success isn’t always about being the fastest, but about finding your own path to value, while managing risk and cost. Join our Gartner’s Opening Keynote to discover how a thoughtful approach to speed and direction helps you prepare for what’s next, no matter where you are today.