The AI Governance Playbook: Moving from Reactive Risk to Strategic Resilience

As institutions move past the initial rush of generative AI adoption, the challenge has shifted from rapid experimentation to long-term operational stability. Many organizations now find themselves caught between the promise of innovation and the growing weight of governance drift, where decentralized tools and exception-heavy workflows create unmanaged regulatory and data risks. To thrive, leadership must move beyond reactive risk management toward a model of strategic resilience. This session introduces a practical playbook for building an AI governance framework that scales with the institutional mission, not against it. Attendees will explore how to audit existing AI-driven workflows to identify where ownership boundaries have dissolved and where accountability gaps exist between IT policy and departmental reality. Drawing on empirical findings from partnerships with Stanford, UC Davis, and Rutgers, we examine how to transition from pilot-phase thinking to governed, sustainable systems. Participants will learn to move beyond the bot, focusing on the data stewardship and ethical reasoning required to protect the institution while empowering faculty and staff creativity. Participants will receive a diagnostic lens to ensure AI remains a strategy multiplier rather than a long-term liability. This session is designed for CIOs, CISOs, and Chief Data Officers looking to stabilize their AI foundations and move from surviving the digital shift to leading the strategy.