When should we stop treating each AI problem as a special case?
A workflow can look successful while employees repair every exception behind the scenes. Treat those repairs as evidence about the process, and watch for the same problem showing up again and again.
The accountability panel's challenge to rethink processes is a good reason to look at those repairs closely. Keep a small, approved log of exceptions. Note the type of problem and its consequence, along with how the team completed the task, and leave out unnecessary personal or confidential details.
Go over the log with the people doing the repairs. Ask whether the same missing information keeps appearing, or a source conflict, or a stuck approval. A recurring issue may belong upstream of the AI step.
Fix the process upstream
Where the evidence supports a structural change, make it. Clarify an intake question, remove a contradictory source or revise the assignment's scope. Adding a longer instruction at the end of the workflow shouldn't be the only response.
Test whether the change reduces the specific problem without hiding it, and keep a route for exceptions that need judgment. The goal is a process that learns from repeated work, with no invisible employee effort holding it together.
What to try this week
Pick one workflow that uses AI and start an exception log for it. Ask whoever repairs the exceptions to add a line each time one comes up.