Practical guide
AI fluency for financial controllers: assemble a review pack
Practice a fictional close-review handoff that keeps reconciliations, open items and sign-off status separate.
A financial controller can use AI to assemble a review pack without allowing a summary to hide unresolved items or imply approval. This original exercise concerns fictional internal reporting records. It is educational coordination practice, not an accounting conclusion, audit opinion or replacement for the organization's authorized professional review.
Define what the review pack must show
Separate completed preparation from evidence that a reviewer has accepted the work.
The fictional pack has three schedules. Schedule A reconciles to its supplied source and has preparer confirmation. Schedule B contains an unexplained difference of twenty units. Schedule C has been revised, but the reviewer comment refers to the earlier version. No final sign-off is recorded.
Ask AI to summarize status by schedule. Reject a single green overall status based on two favorable-looking documents. The review owner needs to see the unresolved difference and the version mismatch, not an average impression of readiness.
Preserve the open-item trail
An unexplained difference should remain an explicit question.
For B, record the amount, compared sources, investigation performed and next owner. Do not invent an adjustment to force the schedules to agree. The exercise supplies no basis for an accounting treatment, so the appropriate artifact is an open-item note.
Keep the source figures and the difference calculation accessible. A summary that says minor issue without explaining the item could conceal information the reviewer considers material. The controller should use the responsible review framework rather than having AI assign materiality from an isolated number.
Match review comments to document versions
A review of an earlier artifact is not automatically a review of the revised one.
For C, identify what changed and which version the existing comment covers. Ask the reviewer to confirm whether the revision needs renewed review under the exercise's process. Do not copy the old approval label onto the new document merely because the filename is similar.
AI can compare versions and draft a change summary. Inspect whether the summary includes the actual changed figures or assumptions. The purpose is to help the reviewer target attention, not to let automated comparison stand in for the review decision.
Prepare a decision-oriented cover note
The cover note should tell the reviewer what is ready and what needs action.
List A as prepared with its evidence, B as unresolved and C as awaiting version-specific review. Identify the final sign-off as pending. Use separate status fields for preparation, reconciliation and review so a single completion checkbox cannot erase those distinctions.
Ask AI to shorten the note, then check every status word. Ready for review, reviewed and approved are not synonyms. Keep the requested next action and owner visible for each incomplete item.
Test the pack after one issue closes
Closing one question should not imply that every other condition has been satisfied.
Add a fictional explanation resolving B's difference with a traceable source correction. Update B's record and preserve the change note. C still needs the relevant review, and overall sign-off remains pending until the authorized owner provides it.
Deliver the cover note, schedule index, open-item log and version references. Review completeness and status discipline within this case. The broader finance guide maps several task families; this role exercise focuses on the integrity of a review handoff, not the professional conclusions the reviewer may later make.
Sources and scope
The references below are background reading, not evidence that this fictional exercise has been validated or endorsed.
The case details, calculations and suggested review questions are original instructional material. Use them to discuss observable work, not to infer customer outcomes, professional credentials or performance in every setting. Before adapting the exercise, confirm the relevant facts, approved tools, data permissions and decision owners. If you change the case, revisit the expected answers and checks as well. These examples describe practice tasks, not a promise that a particular product includes the fictional features.
Sources: [1] [2]
Sources
- 1.AI RMF Core · NIST
- 2.AI foundation skills for work benchmark · Skills England