An AI add-on should be evaluated at the points where a workflow does not run straight through. In the cited approval example, a flow starts and then waits for the approvers’ response before the run completes; another cited source presents human-oversight processes as processes to define, assess, and document. Those exceptions should shape the selection check from the beginning.
Start with the approval boundary
An approval wait is not merely a delay. It is a point where a run has started but cannot complete until the required response arrives.
Before an add-on is considered a fit, map the approval boundary in the actual workflow:
- Where does the run start?
- At what point does it enter a waiting state?
- What response is required?
- What information must remain available while approval is pending?
- What event allows the run to complete?
The cited example establishes the wait-and-response pattern. It does not establish that a particular add-on can preserve pending work, route an approval, or resume a run. Those capabilities require separate verification.
Make human oversight inspectable
Human oversight presents a different kind of exception: work may reach a point where a person must exercise oversight before the workflow continues.
The second cited source states that processes for human oversight are defined, assessed, and documented. For add-on selection, those terms need concrete workflow answers:
- Defined: Where oversight occurs, who performs it, and what decision must be made.
- Assessed: How the oversight process itself is evaluated.
- Documented: What record is produced and retained.
Simply stating that a person is involved does not establish those three conditions. Nor do they prove that a legal, regulatory, or certification obligation has been met; they are workflow-design checks that the team must apply to its own process.
Map other exceptions the same way
The same method applies to any other exception the team can identify, such as a conditional route, a manual reroute, or an input that sends work down a different path. These are general workflow categories, not claims about any tool’s capabilities.
For each exception, record:
- The condition that triggers it.
- The person or role that handles it.
- The state the work remains in during handling.
- The condition that ends the exception.
- The evidence produced afterward.
This makes hidden branches visible before an add-on is compared with the existing workflow.
What still needs confirmation
A smooth demonstration of the normal path does not establish how an add-on handles exceptions. Product-specific documentation and representative testing are still needed to confirm:
- Whether the add-on fits the exact exception point.
- How pending work and approval states are handled.
- What happens when a response is received.
- How human-oversight records are created and retained.
- Which permissions, operating conditions, and service terms apply.
The cited sources do not provide add-on-specific conclusions about compatibility, price, implementation time, or outcomes. Those points should remain unconfirmed unless the actual documentation and test results support them.
The practical answer is to let every material exception shape the choice. If the team cannot state what triggers the exception, who handles it, what state it remains in, how it ends, and what evidence remains, the add-on has not yet been shown to fit the full workflow.