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What is it?
Exception handling is the part of an automation workflow or AI agent that determines what happens when a situation does not fit within the standard rules. That could be an invoice with a missing VAT number, a candidate whose profile does not match the scoring criteria, or an incoming email the system cannot classify. In all these cases, the exception logic decides whether the system processes the case anyway, sets it aside, or routes it to a team member.
Good exception handling is what distinguishes an automation you can trust from one you have to monitor constantly. Without it, a system will either grind to a halt on unexpected input or push through incorrect outcomes without anyone noticing.
Why it matters for SMEs
No business process is completely predictable. There will always be requests that do not quite fit the standard pattern: a client combining two questions in one form, a supplier using an unusual invoice layout, a candidate with a non-standard work history. Without exception handling, an automated system stumbles on those cases or processes them incorrectly.
- Human oversight stays in the right place. Instead of manually reviewing everything, a team member only assesses the cases the system cannot resolve itself.
- Errors are caught early. A well-designed exception path flags problems before they flow through to a customer, the accounts, or a downstream process.
- Trust in the automation grows. When staff know the system recognises uncertainty and refers it on, they are more willing to let go of the standard cases.
Exception handling is not the most exciting part of an automation project, but it is the part that determines whether the automation is reliable in production.
How it works
Exception handling is designed as part of the workflow itself, not as an afterthought. For each step in the process, the possible deviations are mapped, and for each deviation a decision is made: correct automatically, return to the source, or route to a team member.
- Define the normal path: establish what the system considers valid input and what result is expected.
- Determine deviation criteria: describe which situations fall outside the standard path, such as missing fields, low confidence scores, or unknown values.
- Set up escalation routes: for each type of exception, decide whether the system sets the case aside, sends a notification to a specific person, or logs the incident for later review.
- Build a feedback loop: ensure that team members reviewing exceptions can feed back their outcome, so the system can learn or the rules can be refined.
- Test on edge cases: actively simulate exception situations in a test environment before going live.
A useful rule of thumb: automate the standard 80 percent and design exception handling for the remaining 20 percent. Do not try to automate that 20 percent as well until the pattern of exceptions is well enough understood.
Example in practice
Picture a construction firm automating the processing of incoming invoices. The system matches each invoice against the corresponding purchase order and books it automatically when the amount, supplier, and description align. Invoices that deviate by more than five percent from the purchase order, contain an unknown supplier, or are missing an order number are automatically placed in a separate queue and escalated to the procurement team. The accounts payable clerk only handles those cases rather than checking every invoice manually.
Comparison and misconceptions
Exception handling addresses cases that fall outside the expected business logic; error handling addresses technical failures in execution itself, such as an API that does not respond or a file that cannot be read. In practice, robust workflows need both: exception handling for business logic deviations and error handling for technical failures.
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