Will AI replace computer numerically controlled tool operators?

Unlikely, though parts of the work are changing. About 1h 22m of an 8-hour shift goes to tasks touched by robots. The breakdown: 6m that AI mostly does alone, 1h 16m that robots have done in real workplaces. The other 6h 38m (83%) stays with people. Separately, BLS expects about 9.4% fewer of these jobs by 2035 (all jobs: +3.5%).

AI shows up regularly in 1 of 27 tasks, about 6m of a typical shift. The biggest ones:

• Enter commands or load control media, such as tapes, cards, or disks, into machine controllers to retrieve programmed instructions. (6m a shift, AI mostly does it alone)

For some tasks, yes. Robots have done 4 of this job's tasks in workplaces like this one, about 1h 16m of a typical shift. 14 more tasks have only been done in factory setups built around the machine, so they stay with people here.

• Monitor machine operation and control panel displays, and compare readings to specifications to detect malfunctions. (47m a shift; e.g. Lights-out CNC machining cells (production shop, unattended nights/weekends), in use)
• Listen to machines during operation to detect sounds such as those made by dull cutting tools or excessive vibration, and adjust machines to compensate for problems. (12m a shift; e.g. TMAC installed on a customer's CNC machining center, in use)
• Stack or load finished items, or place items on conveyor systems. (12m a shift; e.g. Universal Robots UR5e at Toolcraft Inc., in use)
• Control coolant systems. (6m a shift; e.g. Haas control coolant M-codes (M08/M09 flood, M88/M89 through-spindle), in use)

6h 38m of a typical shift, or 83%, goes to tasks with no AI or robot evidence yet. No AI usage or robot deployment has shown up for these so far. The biggest:

• Set up and operate computer-controlled machines or robots to perform one or more machine functions on metal or plastic workpieces. (1h 34m a shift)
• Measure dimensions of finished workpieces to ensure conformance to specifications, using precision measuring instruments, templates, and fixtures. (59m a shift)
• Mount, install, align, and secure tools, attachments, fixtures, and workpieces on machines, using hand tools and precision measuring instruments. (41m a shift)
• Stop machines to remove finished workpieces or to change tooling, setup, or workpiece placement, according to required machining sequences. (41m a shift)
• Review program specifications or blueprints to determine and set machine operations and sequencing, finished workpiece dimensions, or numerical control sequences. (18m a shift)

Much of it comes down to where and how the work happens. In-person, hands-on and high-stakes work is where AI and robots have made the least headway so far. In the official O*NET survey of people in this job:

• 86% spend more than half the day on their feet
• 69% use their hands on tools, objects or controls more than half the time
• 63% talk face to face with others every day

We track 1 sourced company move that affects this job. Most recent:

• Sep 9, 2025: CloudNC says over 1,000 machine shops use its AI CNC programming tool (Rolling out)

On Indeed, job postings in the Production & Manufacturing sector are at 124% of their February 2020 level (all U.S. postings: 104%), up 12.6% from a year earlier, as of Oct 9, 2026. BLS separately expects about 13,000 openings a year in this job through 2035. Across all U.S. postings, 7.3% now mention AI skills. Sector postings cover more than this one job and move for many reasons besides AI.

The median pay is about $50,690 a year ($24.37 an hour), 1% below the median for all U.S. jobs ($50,980). Most people in this job earn between $38,140 and $73,890 a year; that range covers the middle 80%. Pay figures are from BLS, May 2025, and vary a lot by state and employer. Pick a state to compare:

BLS projects a decline of 9.4% from 2025 to 2035, compared with 3.5% growth for all jobs. That's about 154,000 jobs in 2035. Even so, it expects about 13,000 openings a year, mostly from people retiring or changing careers. These projections don't single out AI as a cause.

About 169,000 people in the U.S., roughly 0.11% of all workers (BLS, May 2025). That makes it the 193rd largest of the 796 jobs on this site. BLS expects about 154,000 in 2035.

The most common requirement is a high school diploma: about 48% of people in the job said so in the official O*NET survey. O*NET rates the job at level 2 of 5 for preparation, which usually means: high school diploma, some training. Requirements vary by state and employer, especially for licensed work.

These come from the job's official skill ratings and from the tasks that AI and robots touch least today. Building them keeps you strong in the parts of the work that still need a person:

• Skills that matter more here than in most jobs: Operation and Control, Operations Monitoring, Repairing, Equipment Maintenance
• Get strong at the parts of the job that stay with people (listed above), which take 6h 38m of a typical shift
• Tools employers list: Autodesk AutoCAD, Dassault Systemes SolidWorks, Microsoft Excel, Microsoft Office software, Microsoft Outlook
• Learn to use AI well on the tasks where it already shows up in this job (listed above)

These use similar skills, with less of a typical shift touched by AI or robots. Matches come from 109 official ratings of skills, knowledge and work activities, and each needs the same or less preparation unless the official list relates the jobs directly:

• Machinists (29m touched, $59k median pay)
• Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic (18m touched, $49k median pay)
• Forging Machine Setters, Operators, and Tenders, Metal and Plastic (17m touched, $49k median pay)
• Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic (0m touched, $47k median pay)

Each task carries its own evidence label. For this job: 1 observed in real AI use, 4 with robots in real deployments, 22 with no AI or robot evidence found. The minutes per task are estimates, not measured hours, and "no evidence" doesn't prove a task is safe.