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 wat

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 te

Starbucks Korea's Tank Day campaign was AI-generated, but the failure was human. What the crisis teaches about AI marketing governance and real oversight.

The GenAI gold rush is on, and companies making bets on new technologies should consider three paths to AI implementation: Buy off-the shelf, boost with proprietary data and build custom solutions.