After-Action Review for AI Implementations

An after-action review compares what an AI workflow was intended to do with what happened, then assigns a specific follow-up. Use evidence from actual cases. A meeting, a positive summary or a list of open actions does not establish that the system improved.

Four questions for the review

1. What result and constraints did we intend?
2. What happened, including exceptions and failed cases?
3. What evidence explains the difference, and what remains a hypothesis?
4. What will change, who owns it and how will we verify it?

This is a proposed review structure for an AI workflow. It is not a claim about the behavior of all military or civilian teams, a client result or a required meeting duration.

Collect a comparable record

Record the workflow version, input period, case-selection method, expected output and review rubric. Keep preparation, model output, review and final completion separate. A draft produced without escalation is not necessarily a correct result.

Include relevant source records, error categories, access problems, latency, cost and the time spent correcting work. Protect confidential information when collecting examples. A review can use case identifiers and approved excerpts instead of copying every original into another tool.

Worked example: choose the right denominator

The following numbers are fictional and illustrate how two valid calculations can describe different things.

Sixty of eighty drafts passed first review. That is different from sixty of one hundred received items reaching that state. Neither calculation establishes final completion, the correctness of direct escalations or the cost of rework.

The review should name the measure and denominator, then inspect the relevant cases. If the question is end-to-end task success, collect the final outcome for every received item rather than reporting draft acceptance as completion.

Separate a finding from a possible cause

Finding: several failed drafts cite the previous version of a policy. Evidence: the case records and retrieved source identifiers show the older version.

Hypothesis: the document-update process did not remove superseded passages. Verify that by inspecting indexing and retrieval records. A prompt change alone may not repair it.

Proposed action: the search owner will correct the version handling, rerun the failed cases and test additional current-policy questions. The review records the result and whether the change should remain enabled. This is a fictional example, not a report of a customer incident.

An action record people can follow

Case or issue ID:
Expected behavior:
Observed behavior and evidence:
Confirmed cause or unresolved hypothesis:
Proposed change:
Responsible owner:
Due or review date:
Verification cases and acceptance criteria:
Decision: open / verified / stopped / superseded, with reason

An action is verified when the agreed check supports the result, not just when someone marks the implementation task complete. Reopen it if the issue returns or the assumptions change.

Use AI to organize evidence, not invent the review

Organize these approved incident and task records under the four review questions.
Attach each factual statement to its record ID.
Separate observations, hypotheses and proposed actions.
Mark missing measures and unresolved disagreements.
Do not invent a cause, owner, result, deadline or customer outcome.
Do not change the system or mark an action complete.

Have the people responsible for the work review the summary. A generated explanation can sound persuasive while missing a failed case or confusing correlation with cause.

Close the loop before the next review

Begin the next review with open actions and their evidence. Retain the decision to continue, stop or supersede an action and its reason. Choose the review cadence to fit the workflow and its risks, rather than promising that a weekly meeting produces an improvement after a fixed number of weeks.

For a system with retrieval, use the embedding failure categories. For several agents, inspect the handoff and recovery example. Compare results on defined cases before attributing a change to the review process.