AI for finance teams: which tasks to automate first
Updated
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.
| 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 |
| Prepare, examine, or analyze accounting records, financial statements, or other financial reports to assess accuracy, completeness, and conformance to reporting and procedural standards. Core digital task; AI checks accuracy and conformance to standards quickly. Done by accountants. | 70% AI can do it 55 hours a year for each person in the role |
| Evaluate data pertaining to costs to plan budgets. AI models cost data and drafts budget scenarios quickly. Done by financial managers. | 55% AI helps 88 hours a year for each person in the role |
| Examine, evaluate, or process loan applications. Document review and underwriting checks are highly automatable today. Done by financial managers. | 65% AI can do it 58 hours a year for each person in the role |
| Prepare financial or regulatory reports required by laws, regulations, or boards of directors. Regulatory reports are largely templated data; AI drafts, humans sign. Done by financial managers. | 62% AI can do it 56 hours a year for each person in the role |
| Prepare itemized statements, bills, or invoices and record amounts due for items purchased or services rendered. Invoices generated from line item data with little manual work. Done by billing clerks. | 75% AI can do it 77 hours a year for each person in the role |
| Perform bookkeeping work, including posting data or keeping other records concerning costs of goods or services or the shipment of goods. Posting cost and shipment records is routine data entry. Done by billing clerks. | 75% AI can do it 73 hours a year for each person in the role |
| Post stop-payment notices to prevent payment of protested checks. Logging stop-payment requests is structured data entry. Done by billing clerks. | 70% AI can do it 69 hours a year for each person in the role |
| Draw charts and graphs, using computer spreadsheets, to illustrate technical reports. Chart generation from spreadsheet data is routine and readily automated. Done by financial analysts. | 85% AI can do it 65 hours a year for each person in the role |
| Review company records to determine amount of insurance in force on single risk or group of closely related risks. Looking up and totaling in-force coverage across company records is database work. Done by insurance underwriters. | 80% AI can do it 220 hours a year for each person in the role |
| Write to field representatives, medical personnel, or others to obtain further information, quote rates, or explain company underwriting policies. Drafting requests and explanations to agents, medical staff, and others is routine writing. Done by insurance underwriters. | 72% AI can do it 211 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.
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.
- Accountants, 21.7% of the team, score 60 out of 100
- Bookkeepers, 20.5% of the team, score 67 out of 100
- Financial managers, 12.6% of the team, score 49 out of 100
- Billing clerks, 6% of the team, score 59 out of 100
- Financial analysts, 5.4% of the team, score 58 out of 100
- Claims adjusters, 4.8% of the team, score 56 out of 100
- Loan officers, 4.1% of the team, score 63 out of 100
- Financial advisors, 4% of the team, score 60 out of 100
- Insurance claims clerks, 3.2% of the team, score 72 out of 100
- Loan clerks, 2.5% of the team, score 64 out of 100
- Bill collectors, 2.4% of the team, score 65 out of 100
- Payroll clerks, 2.3% of the team, score 64 out of 100
- Insurance underwriters, 1.6% of the team, score 59 out of 100
- Tax preparers, 1.1% of the team, score 69 out of 100
- Financial examiners, 1% of the team, score 49 out of 100
- Financial quantitative analysts, 1% of the team, score 58 out of 100
- Credit analysts, 1% of the team, score 62 out of 100
- Financial risk specialists, 1% of the team, score 60 out of 100
- Tax examiners, 0.8% of the team, score 63 out of 100
- Budget analysts, 0.7% of the team, score 56 out of 100
- New accounts clerks, 0.6% of the team, score 53 out of 100
- Brokerage clerks, 0.5% of the team, score 67 out of 100
- Credit counselors, 0.4% of the team, score 66 out of 100
- Actuaries, 0.4% of the team, score 47 out of 100
- Credit clerks, 0.2% of the team, score 61 out of 100
- Auto damage appraisers, 0.2% of the team, score 48 out of 100
- Controllers, Counted under a related job in US data, score 50 out of 100
- Investment fund managers, Counted under a related job in US data, score 53 out of 100
- Real estate appraisers, Counted under a related job in US data, score 52 out of 100
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
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.