Human + AI: Building Practical Accounting Skills

Educational perspective · Revised September 25, 2026. This article does not report findings from Dr. A Ashour’s doctoral study.

Give an accounting team a task it can practice and a clear standard for checking the result.

Choose a skill you can observe

Start with one activity: checking a generated report summary, documenting an exception, or identifying missing information. Write down what a good result must contain. Avoid treating access to software as evidence of competence.

Practice with fictional records

Prepare a small exercise using invented transactions and a deliberately imperfect summary. Ask learners to compare every amount with the records, identify unsupported explanations, and explain what they would do next. Make it clear that the exercise is hypothetical.

Create a route for uncertainty

Agree on who answers questions, when work should be paused, and where corrections are recorded. A useful debrief asks what was unclear and which instructions need improving. Confidence and speed are worth discussing, but neither should replace checking the output.

Review the learning process

Choose a follow up exercise that uses different fictional records. Compare the types of mistakes and the explanation behind each decision. Use the results to plan the next practice session, rather than assuming one demonstration completes the training.

Further reading

For an external risk management reference, see NIST’s AI Risk Management Framework. The practical prompts above are editorial suggestions, not NIST certification or research findings.

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