Identity Drift: The Silent Failure Mode of Agentic AI

Agentic AI is accelerating faster than most IT organizations can govern — and identity is the first place the cracks are showing. While teams obsess over hallucinations, model accuracy, and prompt security, a far more dangerous threat is quietly expanding inside the enterprise: identity drift. Agentic systems don’t behave like traditional users or service accounts. They learn, adapt, chain actions, and evolve their own operational patterns — but their permissions stay static. That mismatch creates a widening gap between what an agent should be able to do and what it can do. And in that gap lives unmonitored privilege, unpredictable behavior, and the next generation of AI‑enabled breaches. In this session, we’re partnering with ‪@IBM‬ to expose why identity drift is the most overlooked failure mode in agentic AI — and why legacy IAM, manual governance, and static access models are fundamentally unprepared for autonomous actors. What we’ll cover: Why agentic AI breaks traditional identity assumptions How drift emerges in autonomous systems — and why it’s nearly invisible The new lifecycle: birth, evolution, mutation, and retirement of AI agents Why static permissions create dynamic risk How IBM and intiGrow are approaching governance for autonomous identities What IT leaders must implement now to prevent agent‑driven privilege creep This is not a “future state” conversation. Identity drift is already happening inside organizations deploying agentic AI — most just haven’t noticed yet. Speakers Bob Kalka, Global Leader, IBM Security Jim Skidmore, VP Solutions Group, intiGrow #ibm #intigrow #agenticai #ai #identity #governance #agents #webinar #virtual #event