We’ve got five departments that need to migrate workflows together. Finance, operations, supply chain, HR, and customer service. The dependency map is a mess—finance needs supply chain data before they can close out certain workflows, HR has to coordinate with finance on payroll timing, operations touches everything.
I’ve been reading about using autonomous AI agents to coordinate multi-department efforts. The idea is that instead of having teams manually coordinate who goes first, what dependencies to manage, what data flows where, you set up agents that can reason through the dependencies and orchestrate the actual workflow sequencing.
What I’m trying to understand is: where does this actually break down? Is it just a coordination tool, or can it actually make intelligent decisions about sequencing? Like, if the system detects a bottleneck—say, finance can’t start because they’re waiting on supply chain data that’s delayed—can the agent actually make a decision to resequence, or does it just flag the problem and wait for a human to solve it?
Also, governance. If you’re letting AI agents make decisions about process flow and sequencing across departments, who’s accountable when something goes wrong? How do you maintain audit trails? Can you trace back why a particular decision was made?
Has anyone actually used autonomous agents to orchestrate a large migration rather than just using them for specific workflow tasks? What actually worked, and where did you still need human intervention?