# Will production clerks be replaced by AI? Updated October 2026 Production clerks score 63 of 100 for AI exposure. The largest share of their task time, 70%, is work AI speeds up while they stay in charge. AI can take over the other 30% outright. - **30%** AI can do it - **70%** AI helps High exposure Higher than 94% of the 923 occupations we scored. ## Task by task We graded 17 tasks, listed here from most to least exposed. AI can do 6 of them today, speeds up 11 and leaves 0 to people. | Task | AI exposure | | --- | --- | | Compile information, such as production rates and progress, materials inventories, materials used, or customer information, so that status reports can be completed. Pulling production and inventory data into status reports is routine. | 82% AI can do it | | Calculate figures, such as required amounts of labor or materials, manufacturing costs, or wages, using pricing schedules, adding machines, calculators, or computers. Calculating labor, material, and cost figures suits AI tools well. | 81% AI can do it | | Record production data, including volume produced, consumption of raw materials, or quality control measures. Logging production volumes and QC readings is structured data entry. | 78% AI can do it | | Compile and prepare documentation related to production sequences, transportation, personnel schedules, or purchase, maintenance, or repair orders. Generating production and purchase paperwork from data is highly automatable. | 76% AI can do it | | Distribute production schedules or work orders to departments. Routing schedules and work orders is mostly digital distribution. | 74% AI can do it | [See what AI can take on across a procurement team](https://www.aigentcy.com/ai-for/procurement/) ## How production clerks compare All occupations (923) Office and administrative support (51) **Production clerks score 63**, 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 $59,650 a year, May 2025 People employed 390,160 in the US, May 2025 Projected change in jobs \-1.3% from 2024 to 2034 ## Skills to build - Build status reports in Microsoft Excel from production data - Run schedule revisions in SAP software during material shortages - Hold progress meetings with department supervisors on completion dates - Verify shipment details with suppliers by phone and email - Inspect incoming materials against specifications before sign-off ## Safer roles nearby 5 related occupations with lower scores. - [Project managers53 out of 100](https://www.aigentcy.com/ai-exposure/project-managers/) - [Shipping clerks47 out of 100](https://www.aigentcy.com/ai-exposure/shipping-clerks/) - [Warehouse supervisors40 out of 100](https://www.aigentcy.com/ai-exposure/warehouse-supervisors/) - [Production supervisors43 out of 100](https://www.aigentcy.com/ai-exposure/production-supervisors/) - [Inventory checkers30 out of 100](https://www.aigentcy.com/ai-exposure/inventory-checkers/) ## Questions about production clerks and AI Will AI replace production clerks? Partly. About 6 in 10 working hours go to tasks AI can already do, mostly compiling status reports and calculating labor and cost figures. Supervisor meetings, supplier calls and negotiated schedule changes stay with people because they need live judgement and agreement. Which production clerk tasks is AI taking over? Compiling status reports from production and inventory data scores 82 on exposure, the highest in this job. Calculating labor, material and cost figures scores 81 because pricing schedules are structured inputs that software processes quickly. Recording production volumes and quality readings scores 78 and is structured data entry. Which production clerk tasks stay human? Conferring with department supervisors scores only 22 on exposure, the lowest in this job. Live meetings need a person to read progress, weigh delays and agree changes. Calls with vendors and customers to resolve delays score 33 for the same reason, because settling problems takes live negotiation. How can production clerks stay valuable? Take on the supplier calls that verify shipment details, which score 52 and still need phone follow-up. Lead schedule revisions when shortages force a new plan, using SAP software to rebuild the schedule and then negotiating changes with sales and production. Physically check incoming parts against specifications, since product inspection stays human. ## Related jobs - [Administrative supervisors55 out of 100](https://www.aigentcy.com/ai-exposure/administrative-supervisors/) - [Maintenance supervisors44 out of 100](https://www.aigentcy.com/ai-exposure/maintenance-supervisors/) - [Procurement clerks65 out of 100](https://www.aigentcy.com/ai-exposure/procurement-clerks/) - [Industrial engineering technicians43 out of 100](https://www.aigentcy.com/ai-exposure/industrial-engineering-technicians/) ## Next steps for production 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.