# AI for operations teams: which tasks to automate first Updated October 2026 Across the 13 million US jobs in operations and admin, the work scores 55 of 100 for AI exposure, weighted by how many people do each job. AI can take on about 912 hours a year per full-time person, 46% of a working year. The task that frees the most hours across the team is to review financial statements, about 99 hours a year for each person who does it. AI exposure, weighted by employment 55 out of 100 High exposure Hours AI can take on 912 hours a year per full-time person Task time AI can do today 21% AI speeds up another 69% ## Tasks to automate first The 15 tasks where AI can take on the most hours across operations and admin: 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 | | --- | --- | | Review financial statements, sales or activity reports, or other performance data to measure productivity or goal achievement or to identify areas needing cost reduction or program improvement. AI can summarize and flag performance data; manager decides actions. Done by general managers. | 58% AI helps 99 hours a year for each person in the role | | Prepare staff work schedules and assign specific duties. Scheduling tools and AI can draft rosters; manager approves assignments. Done by general managers. | 55% AI helps 89 hours a year for each person in the role | | Type, format, proofread, and edit correspondence and other documents, from notes or dictating machines, using computers or typewriters. Dictation, typing, formatting and proofreading are core AI strengths. Done by office clerks. | 80% AI can do it 92 hours a year for each person in the role | | Compute, record, and proofread data and other information, such as records or reports. AI proofreads and checks data well; people spot-check output. Done by office clerks. | 72% AI can do it 88 hours a year for each person in the role | | Answer telephones, direct calls, and take messages. Voice AI can answer, route calls and take messages today. Done by office clerks. | 62% AI can do it 88 hours a year for each person in the role | ## What stays with people 10% 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. - **21%** AI can do it - **69%** AI helps - **10%** Needs a person - Deliver messages and run errands. Office clerks, 6% exposed - Perform sales floor work, such as greeting or assisting customers, stocking shelves, or taking inventory. General managers, 10% exposed - Confer with personnel concerned to ensure successful functioning of newly implemented systems or procedures. Management consultants, 15% exposed - Interview personnel and conduct on-site observation to ascertain unit functions, work performed, and methods, equipment, and personnel used. Management consultants, 20% exposed - Greet visitors, ascertain purpose of visit, and direct them to appropriate staff. Medical secretaries, 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 Approved assistants draft emails, minutes and documents, and summarise long threads. Example: Review financial statements. AI helps with 58% of the time. [AI governance](https://www.aigentcy.com/services/ai-governance/) 2. ### Workflow automation Data entry, document filing, scheduling and approvals run as automations across your systems. Example: Type, format, proofread. AI can do 80% of it. [Process automation](https://www.aigentcy.com/services/process-automation/) 3. ### Agents An agent handles the shared admin inbox, files what arrives and routes each request to the right person. 9 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 operations and admin 21 roles, each linked to its task-by-task score. Of the roles with at least 2% of the jobs, secretaries score highest at 66, administrative services managers lowest at 38. 1. [General managers, 26% of the team, score **44** out of 100](https://www.aigentcy.com/ai-exposure/general-managers/) 2. [Office clerks, 18.3% of the team, score **60** out of 100](https://www.aigentcy.com/ai-exposure/office-clerks/) 3. [Secretaries, 12.7% of the team, score **66** out of 100](https://www.aigentcy.com/ai-exposure/secretaries/) 4. [Administrative supervisors, 10.7% of the team, score **55** out of 100](https://www.aigentcy.com/ai-exposure/administrative-supervisors/) 5. [Project managers, 7.9% of the team, score **53** out of 100](https://www.aigentcy.com/ai-exposure/project-managers/) 6. [Medical secretaries, 7.1% of the team, score **65** out of 100](https://www.aigentcy.com/ai-exposure/medical-secretaries/) 7. [Management consultants, 6.7% of the team, score **55** out of 100](https://www.aigentcy.com/ai-exposure/management-consultants/) 8. [Executive assistants, 3.4% of the team, score **65** out of 100](https://www.aigentcy.com/ai-exposure/executive-assistants/) 9. [Administrative services managers, 2% of the team, score **38** out of 100](https://www.aigentcy.com/ai-exposure/administrative-services-managers/) 10. [Chief executives, 1.5% of the team, score **42** out of 100](https://www.aigentcy.com/ai-exposure/chief-executives/) 11. [Facilities managers, 1.2% of the team, score **42** out of 100](https://www.aigentcy.com/ai-exposure/facilities-managers/) 12. [Data entry clerks, 0.9% of the team, score **66** out of 100](https://www.aigentcy.com/ai-exposure/data-entry-clerks/) 13. [File clerks, 0.5% of the team, score **59** out of 100](https://www.aigentcy.com/ai-exposure/file-clerks/) 14. [Mail clerks, 0.4% of the team, score **25** out of 100](https://www.aigentcy.com/ai-exposure/mail-clerks/) 15. [Typists, 0.3% of the team, score **66** out of 100](https://www.aigentcy.com/ai-exposure/typists/) 16. [Office machine operators, 0.2% of the team, score **33** out of 100](https://www.aigentcy.com/ai-exposure/office-machine-operators/) 17. [Proofreaders, Counted under a related job in US data, score **76** out of 100](https://www.aigentcy.com/ai-exposure/proofreaders/) 18. [Correspondence clerks, Counted under a related job in US data, score **71** out of 100](https://www.aigentcy.com/ai-exposure/correspondence-clerks/) 19. [Desktop publishers, Counted under a related job in US data, score **65** out of 100](https://www.aigentcy.com/ai-exposure/desktop-publishers/) 20. [Chief sustainability officers, Counted under a related job in US data, score **51** out of 100](https://www.aigentcy.com/ai-exposure/chief-sustainability-officers/) 21. [Security managers, Counted under a related job in US data, score **43** out of 100](https://www.aigentcy.com/ai-exposure/security-managers/) ## Questions about AI for operations teams Which tasks should an operations team automate first? The first task to automate is to review financial statements (58% exposed). Next come the tasks to prepare staff work schedules and assign specific duties (55%) and to type, format, proofread (80%). Together they free the most hours across the team. How many hours can AI save an operations team? About 912 hours a year per full-time person, 46% of a 2,000-hour working year. For a team of 10 that is about 9,120 hours, the time of 4.6 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 an operations team are most exposed to AI? Of the roles with at least 2% of the jobs, secretaries score highest, at 66 of 100, and administrative services managers lowest, at 38. Each role's page lists its tasks one by one. Will AI replace jobs in operations and admin? AI can do 21% of the task time across these roles today. Another 69% gets faster with AI while a person stays in charge. 10% needs a person. One task that stays with people is to deliver messages and run errands. Where should an operations team start with AI? With the quick wins: approved assistants for the tasks AI helps with, under a written AI policy. Then automate the 9 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 - [Native AI assistants for business software: guide first, then act](https://www.aigentcy.com/blog/native-ai-assistants-for-business-software/) ### Find the tasks to automate first in your team We map the tasks in your operations 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.