Organizations are charged with being more productive, and while AI is an answer to many such opportunities, organization and program structure can be far more impactful on productivity than using AI. This session will weave together data and analytics governance, MDM, and data quality into one organized initiative that will simplify complexity. Join this session to learn more.

Data governance has traditionally encompassed analytics governance, managing most risks and value in traditional analytics. However, AI introduces new risks and considerations that D&A governance may not be equipped for. Should D&A governance evolve to govern AI or is it time for a separate discipline with a fresh mandate? This session explores conflicting accountabilities, leadership and operating models between these disciplines.

Organizations struggle to make sense of numerous programs and projects that overlap or operate in silos. This research will weave together data and analytics governance, MDM and data quality into one organized initiative that every CDAO should be interested in.