Agentic oversight starts with a simple question: what should a person check before trusting an AI agent with work? This course builds plain-language judgment for everyday staff, including contractors and outsourced staff, so they can tell when an agent is acting, what it may do on its own, and when human review or escalation is required. It focuses on practical oversight checks around disclosure, capability limits, accountability, output review, and live workplace decisions. By the end, learners can judge agent use with confidence instead of treating it like a black box.
The course covers the difference between assistants and agents, irreversible effects, autonomy and reach, point-of-use disclosure, capability boundaries, human accountability, output checking, and proceed-pause-escalate decisions. It also uses a repeatable trust checklist for real workplace scenarios.