How exposed to AI is the job of Engine and Other Machine Assemblers?

6.0% of the weighted task load of Engine and Other Machine Assemblers is exposed, meaning work current AI systems can produce with little structural friction. A further 3.8% is assisted work and 90.2% is untouched. That places it 6th out of 923 occupations, rank 863, in release v2026.Q3 of the Task Exposure Index.

Will AI replace Engine and Other Machine Assemblers?

The index does not measure displacement. It measures what current AI systems can produce and what stands in the way. Whether exposed work becomes a lost job depends on firm economics, regulation and organisational inertia, none of which this index models.

Which tasks of a Engine and Other Machine Assemblers are most exposed to AI?

Of 12 tasks O*NET records for this occupation, 1 are exposed, 0 assisted and 11 untouched. The full task-by-task breakdown is published on this page.

Occupation · SOC 51-2031.00 · Job Zone 2

AI exposure: Engine and Other Machine Assemblers

Construct, assemble, or rebuild machines, such as engines, turbines, and similar equipment used in such industries as construction, extraction, textiles, and paper manufacturing.

Reading this score

computed

Engine and Other Machine Assemblers is among the least exposed occupations measured, at 6.0% of weighted task load, rank 863 of 923. 90.2% of this job is work current AI systems cannot produce at all. That is not a statement about skill or value. It is a statement about what these systems can and cannot do.

What holds the line here is embodiment. Across this occupation's 12 tasks it averages 2.79 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.

The most exposed thing this job does is Read and interpret assembly blueprints or specifications manuals, and plan assembly or building..., at 41.7%. The least is Maintain and lubricate parts or components, at 0.0%. A gap of 41.7% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.

Within production occupations, this one is less exposed than the median of 16.2% across the group's 107 roles, with 98 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.

What would move this score. Of 12 tasks, 1 are currently banded exposed, 0 assisted and 11 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.

Where the score comes from

judged

Every task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.

Dimension	Mean	Scale
Capability	0.38	0-4
Embodiment	2.79	0-3
Presence	0.12	0-3
Accountability	0.50	0-3
Context	1.01	0-3
Verification cost	1.21	0-3

Task by task

12 tasks, O*NET 31.0

Task	Exposed	Assisted	Untouched	Importance	Band
Read and interpret assembly blueprints or specifications manuals, and plan assembly or building operations.	41.7%	20.8%	37.5%	4.65	exposed
Set up and operate metalworking machines, such as milling or grinding machines, to shape or fabricate parts.	15.8%	9.2%	75.0%	3.96	untouched
Inspect, operate, and test completed products to verify functioning, machine capabilities, or conformance to customer specifications.	11.7%	13.3%	75.0%	4.46	untouched
Position or align components for assembly, manually or using hoists.	0.0%	0.0%	100.0%	4.42	untouched
Set and verify parts clearances.	0.0%	0.0%	100.0%	4.40	untouched
Verify conformance of parts to stock lists or blueprints, using measuring instruments such as calipers, gauges, or micrometers.	0.0%	0.0%	100.0%	4.39	untouched
Fasten or install piping, fixtures, or wiring and electrical components to form assemblies or subassemblies, using hand tools, rivet guns, or welding equipment.	0.0%	0.0%	100.0%	4.25	untouched
Remove rough spots and smooth surfaces to fit, trim, or clean parts, using hand tools or power tools.	0.0%	0.0%	100.0%	4.15	untouched
Lay out and drill, ream, tap, or cut parts for assembly.	0.0%	0.0%	100.0%	4.09	untouched
Rework, repair, or replace damaged parts or assemblies.	0.0%	0.0%	100.0%	4.08	untouched
Assemble systems of gears by aligning and meshing gears in gearboxes.	0.0%	0.0%	100.0%	3.96	untouched
Maintain and lubricate parts or components.	0.0%	0.0%	100.0%	3.94	untouched

Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.

Occupations either side of this one

The four closest scores in the same occupational family, then the four closest anywhere in the index.

Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.

What this means in practice

Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.