In the age of Agentic AI, data is no longer just an input to intelligence. It is the foundation that enables autonomous systems to reason, act, collaborate, and make decisions. As organizations embrace AI-driven orchestration, the challenge shifts from managing data assets to creating trusted, real-time, and context-rich data ecosystems. This session will explore how enterprises can modernize data strategy, governance, and operating models to support increasingly autonomous AI systems. Leaders will discuss how to build data capabilities that balance innovation with trust, ensuring that AI decisions remain reliable, explainable, and aligned with business objectives.
Key Discussion Points: - Why Agentic AI requires a shift from static data management to dynamic data operations
- Building real-time, context-aware data foundations for autonomous decision-making
- Modern governance frameworks that balance trust, compliance, transparency, and speed
- Enhancing data quality, lineage, and explainability to support AI accountability
- Creating enterprise-wide data readiness for orchestration-driven business models
- Practical lessons from organizations evolving data strategies to power AI at scale
