# Will knitting machine operators be replaced by AI? Updated October 2026 Knitting machine operators score 28 out of 100 for AI exposure. 60% of their task time needs a person. AI can do 3% and helps with 37%. - **3%** AI can do it - **37%** AI helps - **60%** Needs a person Low exposure Lower than 66% of the 923 jobs we scored. ## Task by task We graded 19 tasks, most exposed first. AI can do 1 of them, helps with 7 and leaves 11 to people. | Task | AI exposure | | --- | --- | | Record information about work completed and machine settings. Logging work and machine settings is routine digital data entry. | 80% AI can do it | | Study guides, loom patterns, samples, charts, or specification sheets, or confer with supervisors or engineering staff to determine setup requirements. AI can read patterns and specs quickly; setter confirms needs and conferrals. | 60% AI helps | | Program electronic equipment. Code assistants can help write machine control programs; engineer reviews output. | 50% AI helps | | Notify supervisors or repair staff of mechanical malfunctions. Sensor alerts and messaging can flag malfunctions to supervisors automatically. | 45% AI helps | | Observe woven cloth to detect weaving defects. Camera fabric inspection assists visual defect spotting; a person still verifies. | 40% AI helps | ## How knitting machine operators compare All jobs (923) Production (107) The dark line is **knitting machine operators, at 28**. Each dot is a score, and darker dots mean more jobs share it. The short marks are the averages, 37 for all jobs and 22 for production. ## Pay and outlook in the US Median pay $39,530 a year, May 2025 People employed 13,030 in the US, May 2025 Projected change in jobs \-13.7% from 2024 to 2034 ## Skills to build - Thread yarn through guides, needles, and rollers manually - Replace worn needles and components with hand tools - Judge cloth defects that camera inspection tools flag - Log machine settings and output in Microsoft Excel - Check machine control programs written by code assistants ## Safer roles nearby 5 related jobs with lower scores. - [Winding machine operators22 out of 100](https://www.aigentcy.com/ai-exposure/winding-machine-operators/) - [Sewing machine operators16 out of 100](https://www.aigentcy.com/ai-exposure/sewing-machine-operators/) - [Paper goods machine operators16 out of 100](https://www.aigentcy.com/ai-exposure/paper-goods-machine-operators/) - [Fiber extrusion operators18 out of 100](https://www.aigentcy.com/ai-exposure/fiber-extrusion-operators/) - [Shoe machine operators13 out of 100](https://www.aigentcy.com/ai-exposure/shoe-machine-operators/) ## Questions about knitting machine operators and AI Will AI replace knitting machine operators? Partly. About 2 in 10 working hours go to tasks AI can already do, mostly logging work and machine settings and reading patterns and specification sheets to set up a run. What stays with people is threading, cleaning, repairing, and judging the cloth, since those tasks need hands and eyes at the machine. Which knitting machine operator tasks does AI take over? Recording work completed and machine settings carries the highest exposure score at 80, because logging is routine digital data entry that software can do automatically. Programming electronic equipment, with an exposure score of 50, is also moving to code assistants that write machine control programs while an engineer reviews the output. Which knitting machine operator tasks stay human? Cleaning, oiling, and lubricating machines has an exposure score of 3, the lowest in the job, because it is physical manual work. Threading yarn through guides and rollers, exposure 8, and inspecting machinery to decide on repairs, exposure 12, also need hands and mechanical judgement at the machine. How can knitting machine operators stay valuable? Learn to thread, level, and align machines manually, since those tasks carry exposure scores of 8 and 5. Get fluent in Microsoft Excel for settings and defect logs, and use Outlook and Word to write malfunction reports engineers can act on. Check every machine control program an assistant writes before it runs on the floor. ## Related jobs - [Fabric cutters31 out of 100](https://www.aigentcy.com/ai-exposure/fabric-cutters/) - [Dye machine operators29 out of 100](https://www.aigentcy.com/ai-exposure/dye-machine-operators/) - [Cutting machine operators22 out of 100](https://www.aigentcy.com/ai-exposure/cutting-machine-operators/) - [Adhesive bonding machine operators22 out of 100](https://www.aigentcy.com/ai-exposure/adhesive-bonding-machine-operators/) ## Next steps for knitting machine operators - ### Check your job Your job title is a rough guide. Your tasks decide your score. Paste your job description or CV to see which 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/) - ### Estimate team savings The score is per person. Add headcount and salary to see the hours AI can take on in a team of knitting machine operators, and what they cost. [Estimate what AI saves a team of knitting machine operators](https://www.aigentcy.com/tools/team-ai-audit/?role=knitting-machine-operators) [Work out the return on automation](https://www.aigentcy.com/tools/ai-savings-calculator/) ### 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**Roustabouts score lowest, at 6.](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**Pediatric surgeons earn a median $559,030 and score 29.](https://www.aigentcy.com/ai-exposure/high-paying-jobs-low-ai-exposure/) - [**Entry-level jobs with low AI exposure**Roustabouts need little prior training and score 6.](https://www.aigentcy.com/ai-exposure/entry-level-jobs-low-ai-exposure/) - [**Jobs AI speeds up the most**AI helps with 98% of the task time for health informatics specialists.](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 score, by first letter.](https://www.aigentcy.com/ai-exposure/jobs/) - [**AI exposure by industry**Average scores for 22 job 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/) Sources and licences 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.