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Accounting

AI in Accounting and Tax Firms: Document Intake, Close Support, and What Stays Human

By

October 26, 2026

5 min read

The parts of accounting work that AI helps with today are clear: reading client documents, matching transactions, drafting explanations and searching past work. Judgment, sign-off and client advice stay with people. Where it pays off, the confidentiality rules to check first (including Section 7216 for tax return information), and how we would build it.

Private AI
Accounting
Generative AI
Amazon Textract
Tax

Accounting firms are short of people and long on documents. That is a good match for AI, as long as the firm is clear about which steps it automates and which it only assists.

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Where it pays off

Task

What AI does

What a person still does

Client document intake

Classifies uploads and extracts fields from tax forms, statements and invoices

Reviews low-confidence fields and anything unusual

Bank and ledger reconciliation

Suggests matches and flags exceptions with reasons

Resolves exceptions and approves

Variance explanations

Drafts explanations from the ledger and prior periods

Confirms the explanation is true

Research and precedent

Searches the firm's past workpapers and memos with citations

Applies judgment to the current client

Client requests

Drafts the "documents still needed" list and follow-ups

Sends, and handles the conversation

Check these first

  • Section 7216 of the Internal Revenue Code restricts how tax return preparers use and disclose tax return information. Confirm with your advisers how AI tools and vendors fit your consent forms and procedures.

  • Professional standards on confidentiality and documentation still apply to AI-assisted work.

  • The FTC Safeguards Rule covers the systems that hold client information, including any AI system.

  • Vendor terms: whether inputs are retained or used for training, and where data is processed.

How we would build it

  1. Start with intake: Textract for forms and tables, a model on Bedrock for narrative documents, with a review queue.

  2. Keep everything in the firm's own AWS account, with client-level permissions and an audit log.

  3. Measure field-level accuracy on a few hundred real documents before reducing review.

  4. Add search over past workpapers once permissions are reliable.

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As of October 26, 2026. Provided as is, for general information, and accurate to the best of our knowledge on the date shown. Not legal, compliance, tax, financial or other professional advice. Prices, limits and vendor services change; check current vendor documentation before relying on anything here. Terms of use.