# AI for finance teams: which tasks to automate first Updated October 2026 Across the 6.7 million US jobs in finance and accounting, the work scores 60 of 100 for AI exposure, weighted by how many people do each job. AI can take on about 1,030 hours a year per full-time person, 52% of a working year. The task that frees the most hours across the team is to match order forms with invoices, about 74 hours a year for each person who does it. AI exposure, weighted by employment 60 out of 100 High exposure Hours AI can take on 1,030 hours a year per full-time person Task time AI can do today 33% AI speeds up another 59% ## Tasks to automate first The 15 tasks where AI can take on the most hours across finance and accounting: how exposed each task is, how much of the job it takes and how many people do that job. Hours are per person in the role that does the task. [How we score each task](https://www.aigentcy.com/ai-exposure/methodology/). | Task and who does it | AI exposure | | --- | --- | | Match order forms with invoices, and record the necessary information. Three way matching of orders to invoices is highly automatable. Done by bookkeepers. | 80% AI can do it 74 hours a year for each person in the role | | Check figures, postings, and documents for correct entry, mathematical accuracy, and proper codes. AI checks figures and codes quickly; person confirms exceptions. Done by bookkeepers. | 68% AI can do it 72 hours a year for each person in the role | | Perform financial calculations, such as amounts due, interest charges, balances, discounts, equity, and principal. Interest, balance and discount formulas are fully automatable. Done by bookkeepers. | 72% AI can do it 70 hours a year for each person in the role | | Process invoices for payment. Invoice data capture and matching is highly routine digital work. Done by accountants. | 85% AI can do it 59 hours a year for each person in the role | | Review accounts for discrepancies and reconcile differences. Reconciliation is pattern matching across ledgers; highly automatable today. Done by accountants. | 72% AI can do it 56 hours a year for each person in the role | ## What stays with people 8% of the task time across these roles needs a person, and the output of the rest still needs someone to check it. The tasks below take the most of that time. - **33%** AI can do it - **59%** AI helps - **8%** Needs a person - Plan, direct, or coordinate the activities of workers in branches, offices, or departments of establishments, such as branch banks, brokerage firms, risk and insurance departments, or credit departments. Financial managers, 20% exposed - Confer with company officials about financial and regulatory matters. Accountants, 18% exposed - Network within communities to find and attract new business. Financial managers, 12% exposed - Direct activities of personnel engaged in filing, recording, compiling, and transmitting financial records. Accountants, 18% exposed - Route statements for mailing or over-the-counter delivery to customers. Billing clerks, 15% exposed ## Adoption path Start with the tasks where AI helps a person, then automate the routine ones, then give whole workflows to agents with a person approving the output. 1. ### Quick wins Give the team an approved assistant for variance commentary, board pack drafts and audit queries, with a written rule on what data it may see. Example: Evaluate data pertaining to costs to plan budgets. AI helps with 55% of the time. [AI governance](https://www.aigentcy.com/services/ai-governance/) 2. ### Workflow automation Invoice capture, matching invoices to purchase orders and bank reconciliation run as automations, and a person clears the exceptions. Example: Match order forms with invoices. AI can do 80% of it. [Process automation](https://www.aigentcy.com/services/process-automation/) 3. ### Agents An agent works through the month-end checklist, chases missing receipts and drafts the management accounts for review. 14 of the 15 tasks on this page are ones AI can do end to end, the work an agent takes on. [Private AI](https://www.aigentcy.com/services/private-ai/) ## Roles in finance and accounting 29 roles, each linked to its task-by-task score. Of the roles with at least 2% of the jobs, insurance claims clerks score highest at 72, financial managers lowest at 49. 1. [Accountants, 21.7% of the team, score **60** out of 100](https://www.aigentcy.com/ai-exposure/accountants/) 2. [Bookkeepers, 20.5% of the team, score **67** out of 100](https://www.aigentcy.com/ai-exposure/bookkeepers/) 3. [Financial managers, 12.6% of the team, score **49** out of 100](https://www.aigentcy.com/ai-exposure/financial-managers/) 4. [Billing clerks, 6% of the team, score **59** out of 100](https://www.aigentcy.com/ai-exposure/billing-clerks/) 5. [Financial analysts, 5.4% of the team, score **58** out of 100](https://www.aigentcy.com/ai-exposure/financial-analysts/) 6. [Claims adjusters, 4.8% of the team, score **56** out of 100](https://www.aigentcy.com/ai-exposure/claims-adjusters/) 7. [Loan officers, 4.1% of the team, score **63** out of 100](https://www.aigentcy.com/ai-exposure/loan-officers/) 8. [Financial advisors, 4% of the team, score **60** out of 100](https://www.aigentcy.com/ai-exposure/financial-advisors/) 9. [Insurance claims clerks, 3.2% of the team, score **72** out of 100](https://www.aigentcy.com/ai-exposure/insurance-claims-clerks/) 10. [Loan clerks, 2.5% of the team, score **64** out of 100](https://www.aigentcy.com/ai-exposure/loan-clerks/) 11. [Bill collectors, 2.4% of the team, score **65** out of 100](https://www.aigentcy.com/ai-exposure/bill-collectors/) 12. [Payroll clerks, 2.3% of the team, score **64** out of 100](https://www.aigentcy.com/ai-exposure/payroll-clerks/) 13. [Insurance underwriters, 1.6% of the team, score **59** out of 100](https://www.aigentcy.com/ai-exposure/insurance-underwriters/) 14. [Tax preparers, 1.1% of the team, score **69** out of 100](https://www.aigentcy.com/ai-exposure/tax-preparers/) 15. [Financial examiners, 1% of the team, score **49** out of 100](https://www.aigentcy.com/ai-exposure/financial-examiners/) 16. [Financial quantitative analysts, 1% of the team, score **58** out of 100](https://www.aigentcy.com/ai-exposure/financial-quantitative-analysts/) 17. [Credit analysts, 1% of the team, score **62** out of 100](https://www.aigentcy.com/ai-exposure/credit-analysts/) 18. [Financial risk specialists, 1% of the team, score **60** out of 100](https://www.aigentcy.com/ai-exposure/financial-risk-specialists/) 19. [Tax examiners, 0.8% of the team, score **63** out of 100](https://www.aigentcy.com/ai-exposure/tax-examiners/) 20. [Budget analysts, 0.7% of the team, score **56** out of 100](https://www.aigentcy.com/ai-exposure/budget-analysts/) 21. [New accounts clerks, 0.6% of the team, score **53** out of 100](https://www.aigentcy.com/ai-exposure/new-accounts-clerks/) 22. [Brokerage clerks, 0.5% of the team, score **67** out of 100](https://www.aigentcy.com/ai-exposure/brokerage-clerks/) 23. [Credit counselors, 0.4% of the team, score **66** out of 100](https://www.aigentcy.com/ai-exposure/credit-counselors/) 24. [Actuaries, 0.4% of the team, score **47** out of 100](https://www.aigentcy.com/ai-exposure/actuaries/) 25. [Credit clerks, 0.2% of the team, score **61** out of 100](https://www.aigentcy.com/ai-exposure/credit-clerks/) 26. [Auto damage appraisers, 0.2% of the team, score **48** out of 100](https://www.aigentcy.com/ai-exposure/auto-damage-appraisers/) 27. [Controllers, Counted under a related job in US data, score **50** out of 100](https://www.aigentcy.com/ai-exposure/controllers/) 28. [Investment fund managers, Counted under a related job in US data, score **53** out of 100](https://www.aigentcy.com/ai-exposure/investment-fund-managers/) 29. [Real estate appraisers, Counted under a related job in US data, score **52** out of 100](https://www.aigentcy.com/ai-exposure/real-estate-appraisers/) ## Questions about AI for finance teams Which tasks should a finance team automate first? The first task to automate is to match order forms with invoices (80% exposed). Next come the tasks to check figures, postings (68%) and to perform financial calculations (72%). Together they free the most hours across the team. How many hours can AI save a finance team? About 1,030 hours a year per full-time person, 52% of a 2,000-hour working year. For a team of 10 that is about 10,300 hours, the time of 5.2 full-time people. The figure is the share of task time AI can remove today, weighted by how many people do each job. Which roles in a finance team are most exposed to AI? Of the roles with at least 2% of the jobs, insurance claims clerks score highest, at 72 of 100, and financial managers lowest, at 49. Each role's page lists its tasks one by one. Will AI replace jobs in finance and accounting? AI can do 33% of the task time across these roles today. Another 59% gets faster with AI while a person stays in charge. 8% needs a person. One task that stays with people is to plan, direct, or coordinate the activities of workers in branches. Where should a finance team start with AI? With the quick wins: approved assistants for the tasks AI helps with, under a written AI policy. Then automate the 14 tasks on this page AI can do end to end. An AI audit maps the tasks in your team and ranks them the same way this page does. ## Next steps - [Case study: purchase orders and invoice checks](https://www.aigentcy.com/case-studies/wholesale-procurement-automation/) ### Find the tasks to automate first in your team We map the tasks in your finance team, score each one the way this page does and build the automations that pay back first. [Book an AI audit](https://www.aigentcy.com/audit/) Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.