Pegasystems has spent decades turning rules, assignments and records into long-running enterprise cases. That history gives Pega a plausible answer to the problem of governing AI agents, but not a free pass. A useful system must keep the right state after a model changes, a connector fails, a policy is revised and a human sends the exception back. The winning metric is not a generated workflow or a fluent recommendation. It is the share of decisions accepted, cases completed correctly and work that does not return to the queue.
