Agentic AI systems promise speed, scale, and automation, but without the right operating model they create new risk faster than most organizations can see it. I will explain how weak governance turns AI initiatives into fragile systems defined by accountability gaps, brittle integrations, activity-based metrics, and decisions that look efficient while increasing operational exposure.
Drawing on my existing frameworks for auditing AI programs, I will tell how to identify governance voids, weak data foundations, and missing strong criteria before they become real business and security problems. I will also walk through practical patterns for production-safe agentic workflows, including confidence scoring, escalation rules, structured audit trails, monitoring dashboards, and controls that keep humans accountable for outcomes. After te session listeners will have a concrete way to evaluate whether their AI program is building resilience.