AI for Tax Accountants: Research, Drafts, and Review

Tax accountants spend significant time on research, drafting positions, preparing correspondence, and reviewing documents. AI can reduce the time each of those tasks takes: summarizing a regulation, drafting a memo explaining a tax position, checking a letter for clarity, or generating a list of questions for a client meeting. The professional judgment, the final review, and the responsibility for the work remain with the licensed accountant.

Setting clear rules for when AI may be used and what it may not handle is the first step, not the last. Tools like fenbs keep those approved review rules alongside the project context, so everyone on the team works from the same boundaries and the rules are available to every connected assistant before it starts work.

Tax research and authority review

Tax research involves finding the applicable code section, regulation, or ruling, understanding what it requires, and determining whether it applies to the client's situation. AI can help with the first part: summarizing what a given IRC section covers, describing the types of transactions a Treasury regulation addresses, or explaining what a recent IRS revenue ruling changed.

The risk in AI-assisted tax research is citation error. AI can produce a confident-sounding summary that cites a code section incorrectly, references a regulation that does not exist, or misses a recent amendment. Every authority cited in an AI response must be verified against the actual source before it is used.

The IRS↗ (opens in a new tab) publishes regulations, revenue rulings, notices, and the Internal Revenue Bulletin. The AICPA↗ (opens in a new tab) publishes standards for tax practice, including Statements on Standards for Tax Services. Both are the authoritative sources that any AI-assisted research needs to be checked against.

Drafting tax memos and correspondence

Tax memos, client letters, and position papers all require clear writing. AI can draft the structure of a memo from a description of the issue, the applicable authority, and the conclusion, producing a first draft that the accountant then reviews, revises, and finalizes. That draft shortens the writing phase significantly without removing the professional's judgment from the final document.

Client correspondence benefits similarly. Letters responding to IRS notices, explaining a tax position, or summarizing a consultation follow standard structures. AI can draft within those structures once you describe the situation, the conclusion, and the key facts. The final letter needs the accountant's review for accuracy and appropriateness before it goes to the client.

Be specific in the prompt. "Draft a memo explaining why the gain on this transaction qualifies for installment sale treatment under IRC Section 453, based on these facts" produces a more usable draft than a general request. The facts you provide determine the quality of the draft; the accountant's knowledge and review determine whether the draft is accurate.

Client data and confidentiality

Taxpayer information is confidential. IRC Section 7216 restricts the use and disclosure of tax return information. Before using an AI tool with any client-specific data, including tax return figures, Social Security numbers, or financial details, the firm must understand how that tool handles data and whether its use complies with Section 7216 and applicable state rules.

The safest approach for general-purpose AI tools is to use them for research and drafting that does not require client-specific data: summarizing a regulation, drafting a template letter, or generating a checklist. For any task that involves client information, use tools with appropriate data processing agreements and legal review.

Drafting that describes a situation without identifying the client ("a client sold a rental property after 10 years and received 20% down at closing") allows AI to draft useful material without including protected data. The accountant then inserts the actual figures in the review step.

Tracking review steps and task status

Tax engagements involve multiple review steps: research completed, memo drafted, senior review done, client approval received. Keeping track of where each step stands, and who completed it, is part of running a clean engagement. AI can help move the work forward; the review log shows that the required steps were taken.

When a task involves multiple people, or an engagement spans weeks, the current status of each item needs to be findable. A review step that was completed last week, or a research question that was answered but not documented, costs time to reconstruct when the next person picks up the work.

For broader guidance on AI governance in professional practice, the AI employees overview and the how-to-use-ai-at-work guide address keeping AI work consistent across teams and longer engagements.

Engagement planning and client preparation

Tax engagement planning involves assembling the information needed before work begins: prior year returns, relevant financial records, changes in the client's situation since last year, and the list of open questions from the previous engagement. AI can generate a tailored information request letter from a description of the engagement type and the client's business structure. The accountant reviews and personalizes that letter before sending it, adding any client-specific context that the general template would not capture.

Client preparation conversations work better when the accountant can anticipate the questions the client is likely to ask and prepare clear answers. Describe the key changes in the client's situation, the relevant tax treatment, and the areas that are likely to need explanation, and ask AI to draft a talking points summary. That preparation means the accountant arrives at the client meeting ready to explain clearly rather than working out the explanation in real time.

Deadline calendars for a tax practice involve multiple clients, multiple jurisdictions, and overlapping filing deadlines that need to be organized clearly. AI can help summarize those deadlines into a structured list, flag extension requests that need to be filed, and draft deadline reminder messages to send to clients. The accountant confirms the accuracy of each deadline against the current year's filing requirements before any deadline goes into a client communication.

Post-engagement review is useful for practice development. After a complex return or an advisory project is completed, asking AI to help structure a brief lessons-learned note, including what information gaps created delays, what questions came up unexpectedly, and what changes would make the next similar engagement run more smoothly, produces practical improvements. That note captures the insight from the engagement rather than letting it evaporate after the filing season ends.

New client onboarding checklists are another area where AI saves preparation time. Describe the client's business type, the services the firm will provide, and any specific compliance requirements, and ask AI to generate a comprehensive onboarding checklist. The accountant reviews and adapts that list to match the firm's standard process and any specific requirements for that client. A consistent onboarding process reduces the risk of missing something that creates problems later in the engagement.

Quarterly review meetings with clients are another planning task that benefits from AI assistance. Before each meeting, reviewing the client's situation from the prior quarter, identifying tax developments that may be relevant, and preparing a short agenda makes the meeting more productive. AI can draft that preparation document from a description of the client's business type and the current quarter's context. The accountant reviews and adds the specific knowledge of the client relationship that makes the document accurate and relevant to the specific client.

How to do this with fenbs

fenbs gives a tax practice team a shared record for approved procedures, engagement context, and task status. No client tax data belongs in it.

1. Create a free account. A team board works for a practice group. Team boards let you assign roles that match your review structure. Personal boards are free with no credit card required.
2. Add a project for each engagement type or practice area. Write the standard review steps, the applicable authority sources, and the AI use rules for that project type.
3. Record the firm's AI use rules in Decisions and rules: what AI may support, what requires senior review, and what must stay outside AI tools. Set the person who approved each rule.
4. Connect a supported AI app from Integrations. Ask the connected assistant to read the engagement context and the current rules before each session so it works within the approved scope.
5. Track research tasks, drafting tasks, and review steps on the board. Move them through the lanes as they are completed and add notes on what was done and by whom, so the engagement record is clear.