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 on its own.“It’s much more like a co-worker than a copilot,” Morgan Stanley Managing Director Todd Johnson said at a recent VB AI Impact event. The internal production agentic system, known as FIXR, goes beyond simple, straightforward “gen AI 1.0” tasks. “We think that’s where the opportunity is to really unlock more complex work in the organization.”FIXR behind the scenesEvery trading day, Morgan Stanley’s trade desks handle the important work around transactions such as cash equities or debt investments. And, at the end of each of those days, controllers must reconcile P&L across the finance giant’s Finance, Risk, Operations, and Trade Capture systems. All that data must come together, and, perhaps not surprisingly, hundreds of thousands of attributes frequently fail to match. Typically, this means controllers must manually investigate each mismatch (or “break”), make decisions on adjustments, then ideally sign off before the number goes to the desk. And all of this while working on a hard morning deadline. Previously, this could take up to six hours for a single book. Now, FIXR performs the task in two to …
