AI exposure: Agricultural Equipment Operators
Drive and control equipment to support agricultural activities such as tilling soil; planting, cultivating, and harvesting crops; feeding and herding livestock; or removing animal waste. May perform tasks such as crop baling or hay bucking. May operate stationary equipment to perform post-harvest tasks such as husking, shelling, threshing, and ginning.
Reading this score
computedAgricultural Equipment Operators is among the least exposed occupations measured, at 7.3% of weighted task load, rank 842 of 923. 86.4% 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 17 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 Irrigate soil, at 26.2%. The least is Position boxes or attach bags at discharge ends of machinery to catch products, removing and..., at 0.0%. A gap of 26.2% 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 farming, fishing and forestry occupations, this one is less exposed than the median of 10.8% across the group's 12 roles, with 7 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 17 tasks, 0 are currently banded exposed, 0 assisted and 17 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
judgedEvery 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 | 0.65 | 0-4 |
| Embodiment | 2.79 | 0-3 |
| Presence | 0.53 | 0-3 |
| Accountability | 0.65 | 0-3 |
| Context | 1.09 | 0-3 |
| Verification cost | 1.00 | 0-3 |
Task by task
17 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Irrigate soil, using portable pipes or ditch systems, and maintain ditches or pipes and pumps. | 26.2% | 11.2% | 62.5% | 3.95 | untouched |
| Weigh crop-filled containers, and record weights and other identifying information. | 25.0% | 12.5% | 62.5% | 4.04 | untouched |
| Guide products on conveyors to regulate flow through machines, and to discard diseased or rotten products. | 16.7% | 8.3% | 75.0% | 4.01 | untouched |
| Adjust, repair, and service farm machinery and notify supervisors when machinery malfunctions. | 15.8% | 9.2% | 75.0% | 4.05 | untouched |
| Manipulate controls to set, activate, and adjust mechanisms on machinery. | 13.3% | 11.7% | 75.0% | 4.27 | untouched |
| Operate towed machines such as seed drills or manure spreaders to plant, fertilize, dust, and spray crops. | 13.3% | 11.7% | 75.0% | 4.15 | untouched |
| Drive trucks to haul crops, supplies, tools, or farm workers. | 13.3% | 11.7% | 75.0% | 4.03 | untouched |
| Observe and listen to machinery operation to detect equipment malfunctions. | 10.0% | 15.0% | 75.0% | 4.31 | untouched |
| Direct and monitor the activities of work crews engaged in planting, weeding, or harvesting activities. | 10.0% | 15.0% | 75.0% | 4.18 | untouched |
| Operate or tend equipment used in agricultural production, such as tractors, combines, and irrigation equipment. | 7.5% | 5.0% | 87.5% | 4.16 | untouched |
| Walk beside or ride on planting machines while inserting plants in planter mechanisms at specified intervals. | 7.5% | 5.0% | 87.5% | 4.03 | untouched |
| Load and unload crops or containers of materials, manually or using conveyors, handtrucks, forklifts, or transfer augers. | 0.0% | 0.0% | 100.0% | 4.53 | untouched |
| Mix specified materials or chemicals, and dump solutions, powders, or seeds into planter or sprayer machinery. | 0.0% | 0.0% | 100.0% | 4.43 | untouched |
| Spray fertilizer or pesticide solutions to control insects, fungus and weed growth, and diseases, using hand sprayers. | 0.0% | 0.0% | 100.0% | 4.33 | untouched |
| Attach farm implements such as plows, discs, sprayers, or harvesters to tractors, using bolts and hand tools. | 0.0% | 0.0% | 100.0% | 3.93 | untouched |
| Load hoppers, containers, or conveyors to feed machines with products, using forklifts, transfer augers, suction gates, shovels, or pitchforks. | 0.0% | 0.0% | 100.0% | 4.24 | untouched |
| Position boxes or attach bags at discharge ends of machinery to catch products, removing and closing full containers. | 0.0% | 0.0% | 100.0% | 3.95 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean. 1 task(s) lacked a usable O*NET weight and are shown but excluded from the weighting.
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.