# Will billing clerks be replaced by AI? Updated October 2026 Billing clerks score 59 of 100 for AI exposure. AI can already do 41% of their task time. Another 40% gets faster with AI, and 19% still needs a person. - **41%** AI can do it - **40%** AI helps - **19%** Needs a person High exposure Higher than 89% of the 923 occupations we scored. ## Task by task We graded 28 tasks, listed here from most to least exposed. AI can do 11 of them today, speeds up 11 and leaves 6 to people. | Task | AI exposure | | --- | --- | | Create billing documents, shipping labels, credit memorandums, or credit forms. Billing documents and credit memos are template driven outputs. | 78% AI can do it | | 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. | 75% AI can do it | | 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. | 75% AI can do it | | Post stop-payment notices to prevent payment of protested checks. Logging stop-payment requests is structured data entry. | 70% AI can do it | | Keep records of invoices and support documents. Digital invoice and support filing is easily automated. | 70% AI can do it | [See what AI can take on across a finance team](https://www.aigentcy.com/ai-for/finance/) ## How billing clerks compare All occupations (923) Office and administrative support (51) **Billing clerks score 59**, marked by the dark line. Each dot is a score, darker where more occupations share it. The short marks show the averages, 37 for all occupations and 57 for office and administrative support. ## Pay and outlook in the US Median pay $48,500 a year, May 2025 People employed 404,060 in the US, May 2025 Projected change in jobs \-0.1% from 2024 to 2034 ## Skills to build - Reconcile billing exceptions and disputes in SAP software - Approve credit memos within set limits in QuickBooks - Build cost reports with pivot tables in Microsoft Excel - Check hospital charges against MEDITECH charge records - Handle physical check batches and mail routing on site ## Safer roles nearby 5 related occupations with lower scores. - [Tellers53 out of 100](https://www.aigentcy.com/ai-exposure/tellers/) - [Administrative supervisors55 out of 100](https://www.aigentcy.com/ai-exposure/administrative-supervisors/) - [Financial managers49 out of 100](https://www.aigentcy.com/ai-exposure/financial-managers/) - [Postal service clerks38 out of 100](https://www.aigentcy.com/ai-exposure/postal-service-clerks/) - [Shipping clerks47 out of 100](https://www.aigentcy.com/ai-exposure/shipping-clerks/) ## Questions about billing clerks and AI Will AI replace billing clerks? Partly. About 5 in 10 of a billing clerk's working hours go to tasks AI can already do, mostly creating billing documents and preparing invoices. Checking exceptions, handling checks and mail, and answering customer disputes stay with people because they need judgement and hands on paper. Which billing clerk tasks is AI taking over? Creating billing documents and credit memos has the highest exposure score, 78, because the output follows fixed templates. Preparing itemized invoices, with a score of 75, follows the same pattern since line items already sit in the system. Posting cost and shipment records, also 75, is routine data entry. Which billing clerk tasks stay with people? Loading machines and stuffing envelopes, with an exposure score of 8, stays with staff because it needs hands on paper and equipment. Weighing envelopes for postage, at 10, and encoding checks on bank machines, at 15, also need a person physically present. Physical handling keeps these tasks with people. How can billing clerks stay valuable as AI spreads? Move toward the work left after AI takes the template tasks. Take on exception review of billing errors in SAP software, approve credit memos within set limits in QuickBooks, and build cost reports in Microsoft Excel pivot tables. Keep hands-on skills in check batch handling and mail routing, which scored 15 or below on exposure. ## Related jobs - [Bookkeepers67 out of 100](https://www.aigentcy.com/ai-exposure/bookkeepers/) - [Customer service representatives74 out of 100](https://www.aigentcy.com/ai-exposure/customer-service-representatives/) - [Insurance claims clerks72 out of 100](https://www.aigentcy.com/ai-exposure/insurance-claims-clerks/) - [Office clerks60 out of 100](https://www.aigentcy.com/ai-exposure/office-clerks/) ## Next steps for billing clerks - ### Check your job Your job title is a rough guide. Your actual tasks decide your score. Paste your job description or CV and see which of your tasks AI can do. [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/) ### Check which roles in your team AI can take on We map your team's tasks, show what AI can do today and build the automations that pay back first. [Book an AI audit](https://www.aigentcy.com/audit/) ## Related topics - [**Jobs AI can't replace**Cement masons score lowest, at 8.](https://www.aigentcy.com/ai-exposure/jobs-ai-cant-replace/) - [**Jobs most at risk from AI**Proofreaders score highest, at 76.](https://www.aigentcy.com/ai-exposure/jobs-most-exposed-to-ai/) - [**High-paying jobs with low AI exposure**Radiologists earn a median $420,860 and score 46.](https://www.aigentcy.com/ai-exposure/high-paying-jobs-low-ai-exposure/) - [**Entry-level jobs with low AI exposure**Cement masons need little prior training and score 8.](https://www.aigentcy.com/ai-exposure/entry-level-jobs-low-ai-exposure/) - [**Jobs AI speeds up the most**For natural sciences managers, AI speeds up 96% of task time.](https://www.aigentcy.com/ai-exposure/jobs-ai-speeds-up/) - [**AI and jobs in Malta**15 iGaming roles graded task by task.](https://www.aigentcy.com/ai-exposure/malta/) - [**Skills that keep work human**The skills to build in the jobs AI changes least.](https://www.aigentcy.com/ai-exposure/skills/) - [**Jobs A to Z**Every job we publish, by first letter.](https://www.aigentcy.com/ai-exposure/jobs/) - [**AI exposure by industry**Average scores for 22 occupation groups.](https://www.aigentcy.com/ai-exposure/industries/) - [**Write a CV screening software can read**How applicant tracking systems read a CV, and what to change.](https://www.aigentcy.com/ai-exposure/cv-screening-guide/) - [**AI for businesses**The tasks to automate first in each team and industry.](https://www.aigentcy.com/ai-for/) - [**How we score AI exposure**The grading, the weights and every source.](https://www.aigentcy.com/ai-exposure/methodology/) 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.