Deploying agentic AI at scale reveals that operational governance—not just implementation—is critical to managing risks like model drift, data degradation, and accountability gaps. Effective governance requires setting evidence-based tolerance limits, training line-of-business managers to oversee AI agents as team members, embedding rapid incident response protocols, and ensuring compliance with legal obligations as ongoing operational practices. Organizations that integrate AI governance into daily operations and assign clear responsibility will sustain AI-driven business benefits and avoid costly failures as regulatory demands tighten.
