Nancy Wang

You built AI agents to be autonomous. That was the point. But autonomy drifts, and in a multi-agent system it drifts at the group level, where every agent still passes its own check and nothing flags a problem. At OpenAI it ran that way for two months. Multi-agent AI governance is a system-level job: reduce the conditions that start drift, put a human only where being wrong is expensive and watch for organization itself appearing between your agents. Most monitoring today watches none of it.

A fundable AI business case makes four things legible to leadership at once: impact, return, real cost and risk. Most initiatives stall because one of the four stays vague. Every AI initiative arrives at the same moment. The exploration is done: the workflow studied, the data evaluated, the vendor landscape reviewed, the fit tested. The initiative seems worth pursuing. Then someone in the room, often you, says: "Great. Let's build the business case." That is where too many teams quietly...

Some 88% of organizations use AI but only 39% see measurable impact. A four-dimension ROAI framework helps leaders prioritize the initiatives that create value.