Short answer
Very unlikely. BLS rates cutting among the occupations least exposed to AI, and most of the work is the kind current AI tools cannot do.
AI and jobs
Will AI Replace Cutting? (2026)
The Bureau of Labor Statistics places cutting in its low AI exposure category, among the occupations least exposed to current AI. BLS projects employment to fall by 10.5% over 2025–2035, against 3.5% for all occupations, with about 13,200 openings a year.
- BLS AI exposure
- LowBLS EP supplemental table
- AI-resilience score
- 43/100Higher than 47% of jobs · NueCareer
- Projected change
- -10.5%BLS EP 2025–2035; all jobs 3.5%
- Openings a year
- 13,200BLS EP 2025–2035
The federal measure
How exposed cutting are to AI
The Bureau of Labor Statistics publishes a relative AI exposure category for each occupation it projects, built from five public measures of where AI could be, or already is, used to assist with or complete the work. Cutting land in the low category: among the occupations least exposed to current AI.
Where this job sits on the BLS scale
786 occupations in the NueCareer bank, in BLS's four relative categories; width shows how many fall in each
- Low · this job203 occupations · 26%
- Moderate194 occupations · 25%
- High190 occupations · 24%
- Very high199 occupations · 25%
Source: BLS Employment Projections, AI exposure categories supplemental table.
- Exposure is relative. The categories rank occupations against each other; they are not a probability that a job is automated.
- BLS says exposure does not imply job loss, productivity gains, automation probability or wage effects. A highly exposed job can still grow if AI makes the people in it more productive.
- The classification reflects AI capabilities as the underlying studies measured them. Read the BLS method and limitations.
Inside the work
What AI can and cannot do in this job
O*NET rates how important each work activity is to an occupation and how often each working condition comes up. The ratings below are the ones that move the job's NueCareer AI-resilience score the most: the ones that pull it up, and the ones that pull it down. Only ratings clearly above the midpoint count.
What holds up
Physical, hands-on and person-to-person work
- Hands-on work with tools and objects4.6/5O*NET work context, frequency or level
- Face-to-face discussions4.0/5O*NET work context, frequency or level
- Handling and moving objects3.9/5O*NET work activity, importance
- Performing general physical activities3.5/5O*NET work activity, importance
What AI reaches first
Routine, repeatable and screen-based work
- Repeating the same tasks4.1/5O*NET work context, frequency or level
- Repetitive motions4.5/5O*NET work context, frequency or level
- Being exact or highly accurate4.4/5O*NET work context, frequency or level
- Getting information3.5/5O*NET work activity, importance
The tasks O*NET lists for cutting
- Clean work area.
- Set up, operate, or tend machines to saw, cut, shear, slit, punch, crimp, notch, bend, or straighten metal or plastic material.
- Examine completed workpieces for defects, such as chipped edges or marred surfaces and sort defective pieces according to types of flaws.
- Start machines, monitor their operations, and record operational data.
- Measure completed workpieces to verify conformance to specifications, using micrometers, gauges, calipers, templates, or rulers.
- Read work orders or production schedules to determine specifications, such as materials to be used, locations of cutting lines, or dimensions and tolerances.
O*NET 31.0 Database task statements, most important first.
The jobs
Will there still be jobs?
Exposure says where AI meets the work. The BLS projection says what the labor market is expected to do over 2025–2035. BLS projects -10.5% change in employment over the decade, against 3.5% across all occupations, and about 13,200 openings a year once retirements and career changes are counted. About 171,200 people work in the job today, at a median of $46,330 a year (BLS OEWS, May 2025).
Options
Related careers that are also low-exposure
Careers O*NET lists as related to the work, or in the same field at similar pay, that BLS places in a low exposure category.
Grinding and Polishing Worker, Hand
Production
- Median pay
- $42,660median a year
- Growth
- −19.2%
- Openings / yr
- 700
- Education
- No formal credential
- Low
- BLS AI exposure
- 68/100
- resilience
Grind, sand, or polish, using hand tools or hand-held power tools, a variety of metal, wood, stone, clay, plastic, or glass objects.
- Median pay
- $43,380median a year
- Growth
- −2.5%
- Openings / yr
- 5,300
- Education
- High school
- Low
- BLS AI exposure
- 48/100
- resilience
Set up, operate, or tend woodworking machines, such as drill presses, lathes, shapers, routers, sanders, planers, and wood nailing machines.
- Median pay
- $49,030median a year
- Growth
- −17.2%
- Openings / yr
- 600
- Education
- High school
- Low
- BLS AI exposure
- 48/100
- resilience
Set up, operate, or tend forging machines to taper, shape, or form metal or plastic parts.
- Median pay
- $46,550median a year
- Growth
- −10.8%
- Openings / yr
- 4,500
- Education
- High school
- Low
- BLS AI exposure
- 47/100
- resilience
Set up, operate, or tend grinding and related tools that remove excess material or burrs from surfaces, sharpen edges or corners, or buff, hone, or polish metal or plastic work pieces.
Questions
Will AI Replace Cutting? FAQ
Will AI replace cutting?
Very unlikely. BLS rates cutting among the occupations least exposed to AI, and most of the work is the kind current AI tools cannot do. BLS defines exposure as AI being able to assist with or complete some of the work, and says it does not imply job loss, productivity gains or wage effects. BLS projects employment to fall by 10.5% over 2025–2035, against 3.5% for all occupations, with about 13,200 openings a year.
How exposed are cutting to AI?
BLS sorts 786 occupations into four relative categories: low, moderate, high and very high. Cutting are in the low category, alongside 202 other occupations. The categories combine five public measures of where AI could be or already is used, and they compare occupations with each other rather than giving an absolute risk.
What parts of a cutting, punching, and press machine setter, operator, and tender, metal and plastic's job can AI do?
In O*NET's description of the work, the parts that overlap most with what AI handles well are repeating the same tasks, repetitive motions and being exact or highly accurate. The parts that hold up best are hands-on work with tools and objects, face-to-face discussions and handling and moving objects. These come from O*NET ratings of how important each activity is to the job, read through NueCareer's AI-resilience method.
Is being a cutting, punching, and press machine setter, operator, and tender, metal and plastic a safe career from AI?
On NueCareer's AI-resilience score, built from O*NET work activities, cutting score 43 out of 100, higher than 47% of the occupations we score. The job pays a median of $46,330 a year (BLS OEWS, May 2025). No job is fully safe from technological change, but the federal exposure category and the projected openings are the two numbers worth weighing.
What careers similar to cutting are less exposed to AI?
Grinding and Polishing Worker, Hand (low exposure, $42,660 median), Woodworking Machine Setter, Operator, and Tender, Except Sawing (low exposure, $43,380 median), Forging Machine Setter, Operator, and Tender, Metal and Plastic (low exposure, $49,030 median), Grinding, Lapping, Polishing, and Buffing Machine Tool Setter, Operator, and Tender, Metal and Plastic (low exposure, $46,550 median). Each is also in the low category, and most are listed by O*NET as related to the work.
The AI exposure category is the Bureau of Labor Statistics'. The AI-resilience score and the activity breakdown are NueCareer's analysis of O*NET 31.0 Database data (method), not a federal figure. More: jobs most exposed to AI, jobs least exposed to AI, or check any job.