How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is moderately exposed to automation, and meaningful change looks likely over the next 5 to 10 years.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 1.3 to 25.3
Physical / roboticsrange 51.9 to 75.9
When the change is likely
Partial, 5 to 10 yearslocal demand stable
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Use your 5 to 10 year runway
Change here is gradual. Build resilient skills steadily and watch the signals rather than waiting for a shock.
2
Move up from the task to the system
Robotics targets the physical work. Shift toward supervising, maintaining, or programming the automation instead of competing with it.
It is skill-adjacent and less exposed (45.9 vs 64). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
Keep the monitor on
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Which of my tasks are exposed
Calculate dimensions or tolerances, using instruments, such as micrometers or vernier calipers.
63.9
Machine parts to specifications, using machine tools, such as lathes, milling machines, shapers, or grinders.
63.9
Measure, examine, or test completed units to check for defects and ensure conformance to specifications, using precision instruments, such as micrometers.
63.9
Set up, adjust, or operate basic or specialized machine tools used to perform precision machining operations.
63.9
Program computers or electronic instruments, such as numerically controlled machine tools.
63.9
Study sample parts, blueprints, drawings, or engineering information to determine methods or sequences of operations needed to fabricate products.
63.9
Monitor the feed and speed of machines during the machining process.
63.9
Maintain machine tools in proper operational condition.
63.9
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Calculate dimensions or tolerances, using instruments, such as micrometers or vernier calipers.
Task: Machine parts to specifications, using machine tools, such as lathes, milling machines, shapers, or grinders.
Lower-risk adjacent roles
Computer Numerically Controlled Tool Programmers
45.9
Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic
50.4
Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic
56.0
Tool and Die Makers
56.2
Computer Numerically Controlled Tool Operators
59.7
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map Machinists to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 13.3, robotics 63.9.
The timeline comes from the higher axis (63.9), shifted for local demand (stable), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.