To achieve agentic optimization, D&A leaders must invest in active metadata and data ecosystems, develop FinOps maturity, and train AI models. This foundation enables efficient, automated decision-making for deploying and optimizing D&A resources. This session explores how these areas intersect, offering a holistic view of agentic capabilities, impacts and risks. Go beyond targeted agents and think big!

D&A leaders struggle to prioritize and justify data management spend, especially amid cloud-driven cost unpredictability. Value stream analysis links data production to direct and indirect business outcomes, driving quantifiable benefits. This session will link core research on cost management and FinOps with a means of using active metadata to measure value resulting in holistic cost optimization.

AI spending continues unabated and so is the pressure on leaders. CIOs need to demonstrate the value of AI. CFOs need to calculate it. The c-suite needs to collaborate to create real value. Here we present Gartner's framework for a rigorous, repeatable approach to financial operations (FinOps) of AI initiatives. The focus is on the economics of business value, cost and risk of AI, GenAI and agentic AI.