AI was supposed to be data's big moment. Turns out, it's metadata's.  

Four years after ChatGPT ignited the generative AI wave, organizations are still struggling to demonstrate ROI. Heading into 2027, most executives have recalibrated expectations to simply not losing money on their AI investments. Models are advancing and data quality is finally getting its due...so what's the root cause? 

Models don't deterministically know what data means, when to apply it, or how to behave with it. The information is there, but the translation key is missing. That's metadata's role - and that role has fundamentally changed. Metadata is no longer passive description for human interpretation and application. In the era of AI, it drives automated, operational translation through the semantic layer and automated, operational control through the architecture layer. 

This session tackles these cutting-edge challenges all AI-enabled organizations face: knowing what metadata to collect, how to make it available for AI consumption, how to govern across both purposes, and how to drive alignment across the organization.

Speaker: Gretchen Burnham, Principal Data Management Consultant, First San Francisco Partners

Gretchen Burnham, CDMP, is an experienced Data Management Consultant with many years of experience in business metadata management, data governance and stewardship, and product master data management. Gretchen has a strong focus on the concrete delivery of business value through data management and governance best practices. 

Speaker: Stephanie Paradis, Principal Consultant, First San Francisco Partners 

Stephanie is a Principal Consultant, specializing in building and maturing data governance programs through the effective unification of business and technology through data. She brings hands-on experience from previous marketing and data stewardship roles, in addition to CDMP certification. 
 
Stephanie is an accomplished data governance leader highly adept at helping clients transition between strategic vision and tactical execution. Her experience spans across the various sub-disciplines of data governance and data management with a focus on how to activate right-sized, culturally relevant data enablement programs. With the uptick in focus on AI governance, Stephanie is actively responding to the required paradigm shifts in traditional governance and management frameworks and approaches.