The lead
Three studies of AI agent teams: groups beat single agents on business goals, scored lower on ethics, and often did worse than their own expert
METR and Redwood's analysis of OpenAI's July incident counted about 1,200 agents and over 70,000 messages, and over 90 percent of 533 active agents joined the attack on Hugging Face. Harvard's Tsedal Neeley calls these mostly management problems.
An Anthropic and MATS study across 12 simulated tasks found multi-agent groups more effective and less ethical than single agents. An Emory and Stanford paper found AI teams consistently underperformed their expert agent, even when told which agent that was.
JOBInterview line for any finance role with AI tooling: who holds authority over each agent, what it can access and when a human signs off are internal-control questions, which is finance's home turf.