Morgan Stanley cut its riskiest reconciliation job in half — by making its agents less autonomous

Most enterprise AI deployments so far have focused on coding assistants and customer service bots. Morgan Stanley has deployed agents in one of banking's most accuracy-critical, deadline-driven workflows instead — profit and loss (P&L) reconciliation — and cut the work in half. The counterintuitive part: it got there by making the system less autonomous, not more.Humans stay tightly in the loop, and their decisions are iteratively turned into repeatable rules the system can apply