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Examples

AI in accounting examples and what stays human

Six accounting tasks where AI does the repetitive part. Each example shows what the AI handles and what the accountant still decides.

Updated 5 min read

The short answer

AI in accounting examples include reading invoices, coding transactions, matching bank records, preparing the month-end close, picking audit samples and drafting client summaries. The AI prepares the work. The accountant reviews it and signs off.

Key points

  • AI handles the repetitive, rule-based steps
  • The accountant keeps judgment and sign-off
  • Begin with the costliest task

Examples

AI in accounting examples by task

Results appear only where a client project or a published source supports them.

  • Accounts payable

    Invoice capture and matching

    AI reads each invoice, matches it to the right case and syncs it to the accounting system. A person checks the exceptions.

    40+hours back every month

    Read the case →

  • Bookkeeping

    Transaction coding

    AI suggests a category for each expense from past entries. The bookkeeper corrects the odd ones, and the next batch gets better.

    Read the case →

  • Reconciliation

    Bank reconciliation

    AI matches bank lines to ledger entries and flags the ones that do not fit, so the team reviews differences instead of every line.

    Read the case →

  • Close

    Month-end close and reporting

    AI gathers the numbers, drafts the standard reports and highlights unusual swings. The controller reviews before anything goes out.

    Read the case →

  • Audit

    Audit sampling and checks

    AI scans a full ledger for odd entries and proposes where to sample. The auditor decides what to test and what it means.

    Read the case →

  • Advisory

    Client advisory drafts

    AI drafts a financial summary or a talking points sheet for a client meeting. The accountant edits it and adds the advice.

    Read the case →

Examples of artificial intelligence in accounting

  • Read documents

    Pull amounts and dates from invoices and receipts.

  • Sort entries

    Suggest categories and match bank lines.

  • Draft output

    Prepare reports and client summaries.

Examples of artificial intelligence in accounting share one pattern: software reads or sorts something, and a person decides.

Thomson Reuters describes firms using AI software to categorize expenses, reconcile accounts and generate financial reports.

Many accounting automation examples start with documents, because invoices and statements arrive in different formats.

What stays with the accountant

AI prepares

  • Reads and sorts documents
  • Suggests codes and matches
  • Drafts reports

Accountant decides

  • Reviews exceptions
  • Judges unusual items
  • Gives client advice

The Bureau of Labor Statistics expects accountants and auditors to see 5 percent job growth from 2025 to 2035.

It also notes that automating routine tasks makes advisory and analytical duties more prominent.

So the split is simple: AI does the routine work, and people keep judgment, client advice and sign-off.

AI use cases in banking and financial services

  • Customer service

    Chatbots answer routine account questions.

  • Credit work

    AI reads documents to support underwriting.

  • Risk and fraud

    Models flag unusual activity for review.

AI use cases in financial services reach past accounting. The Federal Reserve Board puts work-related generative AI use at 63 percent in finance, the highest of any sector, with professional services at 62 percent.

The U.S. Government Accountability Office lists customer service, credit decisions, risk management and fraud work among the activities where institutions use AI.

Automation in banking examples include chatbots and document analysis for credit underwriting. See our financial services work and the AI in financial services guide.

Risks to plan for

Good practice

  • Review AI output before use
  • Test models for bias
  • Keep clear reasons on file

Weak practice

  • Trust every suggestion
  • Use vague decision reasons
  • Skip monitoring

Lending adds rules. The CFPB says creditors cannot use vague checklist reasons when a decision goes against an applicant. The reasons must be specific and accurate.

The GAO also warns that AI models can carry bias into credit decisions, so people need to test and monitor them.

Accountants should review AI output before any client or regulator sees it.

How to pick your first accounting use case

  1. 01

    List tasks

    Write down every repeated finance task.

  2. 02

    Count hours

    Estimate monthly time on each.

  3. 03

    Pick one

    Choose the one with clear rules.

  4. 04

    Review

    Check output, then add the next.

List your repetitive finance tasks and put hours on each. The one that costs most and follows clear rules is the best first candidate.

Our AI consulting engagements open with exactly this kind of costed list. Then you can calculate the automation return before you build.

Our data

What AI answers when buyers ask

We asked ChatGPT, Gemini and Perplexity 10 buyer questions about AI for financial services firms. They named 107 companies, and 72% appeared in only one of the three.

CriterionChatGPTGeminiPerplexity
Companies named494154
Sites cited mostfitsmallbusiness.com (3 of 10)numeric.io (4 of 10)blueprism.com (4 of 10)

Nexum measurement, October 20, 2026, via DataForSEO: 10 buyer questions to each AI, US English, 30 answers in total. 7 companies appeared in all three. Google showed an AI Overview for 9 of the 10 questions.

FAQ

Questions about AI in accounting

  • Firms use AI to read invoices, categorize expenses, reconcile accounts and draft reports and client summaries. A person reviews the output and handles judgment calls and advice.

  • General chat tools can draft explanations or summaries, but accounting data needs care. Do not paste client records into a tool without checking privacy rules, and review every answer before using it.

  • Accountant and auditor jobs should grow 5 percent between 2025 and 2035, BLS projects. Routine tasks get automated, and advisory and analysis work becomes more prominent.

  • Parts of it already are. Clerk roles shrink instead: BLS expects bookkeeping clerk jobs to fall 6 percent over the same decade as software takes over routine entries. Review and judgment remain with people.

  • Common AI use cases in banking include customer service chatbots, credit decisions, risk management and fraud work, according to the GAO. Document analysis can also support credit underwriting.

  • Keep manual anything that needs judgment, client trust or a signature: unusual entries, tax positions and advice. Let AI prepare the routine steps, and have a person confirm before anything is final.

Related

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