When an AI workflow hits an unusual case, what should happen next?
A missing detail, a failed tool, and a policy conflict can interrupt the same workflow for very different reasons. Treat them alike, and you risk letting automation continue beyond its limits or filling human queues with work that could have been resolved another way.
The Exception Layer gives managers, process owners, operations leaders, and accountable professionals a structured method for exception handling in AI-assisted and agentic work.
Its Routine Path Decision Framework connects the conditions that justify ordinary handling with the next mode a case needs, the context that must travel with it, and the conditions for returning to an approved routine.
Across ten chapters, you will learn how to:
- Define the information, scope, permissions, safeguards, and recoverability that make a case eligible for routine handling.
- Distinguish uncertainty, novelty, and missing information from boundaries that prohibit ordinary handling.
- Choose among seven handling modes: continue, constrain, clarify, recover, redirect, refer for judgment, and stop or reverse.
- Weigh the consequences of continuing against the costs of interruption, and identify when expertise or authority needs to reenter.
- Build usable handoffs that preserve case state, material evidence, prior attempts, constraints, and the specific decision required.
- Restore routine handling when eligibility returns, and recognize when recurring exceptions call for a redesigned process.
Three end-to-end composite cases follow customer billing, professional research, and agentic procurement through changing conditions. They show how the framework adapts as information, authority, and consequences change.
The focus is the case moving through a defined workflow: what can proceed, what must change, and what the next person or system needs to act.
Know when to continue, when to change course, and when judgment needs to return.
