AI for small accounting firms: choosing your first workflow

Start with preparation you can check

For a small accounting firm, a sensible first AI workflow is a repeatable preparation task with clear inputs and a result a person can verify. Document organization, a missing-information checklist, or a draft client follow-up are candidates to evaluate. Start with one task and measure the complete process before expanding.

This guide proposes a pilot method, not a claim that every firm will save the same amount of time. The right choice depends on your records, existing software, review requirements, and the people doing the work.

Separate repeatable work from professional judgment

List the tasks your team repeats during a typical engagement. For each task, name the input, expected output, reviewer, and stopping point. “Prepare a list of missing documents from this checklist” is easier to test than “finish the client’s taxes.”

NIST identifies confabulation as a generative AI risk: a system can confidently present false information, including misleading supporting citations. A polished explanation therefore needs verification, rather than being treated as evidence of correctness.NIST: Generative AI Risk Management Profile, section 2.2

• Document intake: propose categories, then check them against the originals.
• Missing-information review: compare received records with an engagement checklist.
• Client follow-up: draft a specific request for a person to approve before sending.
• Workpaper preparation: gather references and unresolved questions for the reviewer.

Define the data boundary before the trial

Canadian privacy authorities’ generative AI principles call for limiting personal information to the identified purpose and establishing accountability for privacy compliance. The principles also recommend using anonymized, de-identified, or synthetic data where possible.Canadian privacy authorities: Principles for generative AI

For an initial trial, our recommendation is to use synthetic examples that resemble your workflow. Before introducing client records, have the responsible person assess the tool, its retention and training settings, access controls, and contractual terms. A privacy setting alone does not establish that a tool is appropriate for your firm.

Run a comparison on the same task

Choose a representative sample rather than only the cleanest files. Include a missing document, an ambiguous entry, and a corrected record. Ask a reviewer to assess whether the agent identifies these cases and preserves enough context to check its output.

Measure the manual process and the assisted process using the same definition of done. Count preparation, checking, corrections, and follow-up time. Record mistakes separately from unresolved questions: an agent that flags uncertainty may be behaving more usefully than one that guesses.

Illustrative calculation: if a manual task takes 90 minutes and assisted preparation takes 10 minutes plus 25 minutes of review, the difference is 55 minutes for that example. This is arithmetic for planning a trial, not a measured JAN AI result.

• Total time from usable input to reviewed output.
• Incorrect or unsupported statements found during review.
• Missing items correctly identified and items overlooked.
• Correction time and the reasons for returning work.

Choose a stopping rule and an owner

Agree in advance which errors stop the trial and who can approve expansion. If the task requires repeated reconstruction of the original records, improve the inputs or narrow the scope. If the reviewer cannot trace a result, fix the handoff before adding volume.

Keep a brief record of the task definition, trial examples, outcomes, and changes made. Repeat the comparison after material changes to the workflow or tool. JAN AI’s direction is to make this kind of delegation practical for smaller firms and business teams, starting with tax and finance preparation.