EXPOSED
Much of the work — irrigation and drainage calculations, CAD drafting of equipment and storage structures, sensor/yield data analysis, grant and permit paperwork, feasibility write-ups — is exactly the structured technical output AI now drafts competently. What holds is the field half: walking fields and feedlots to diagnose why a drainage plan or manure-handling system actually failed, commissioning machinery, and taking responsibility for designs that touch food safety, water rights, and livestock welfare. PE licensure applies to stamped structural and water-resource work but a large share of ag engineers never stamp anything, so the shield is partial.
Roughly flat across the period, with year-to-year wobble.
Median pay $80,720 → $98,590 -2.3% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
+5.9% 1,700 → 1,800 on the projections basis
Growing, and only partly exposed
The BLS expects +5.9% more of these jobs by 2034, and at 52/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~100 openings a year on average, including replacing people who leave.
EngineerTest EngineerField EngineerProduct EngineerProject EngineerRegional EngineerResearch EngineerAgriculture EngineerAgricultural EngineerAgriculture ScientistConservation EngineerPermaculture DesignerAgriculture ConsultantFarm Equipment EngineerField Research AssociateProduct Technology ScientistAgricultural Research EngineerResearch Agricultural EngineerAgricultural Systems SpecialistLandscape Irrigation SpecialistSupplier Quality Engineer (SQE)Agricultural Production EngineerAgricultural Equipment Test EngineerAgricultural Equipment Design Engineer
Holding it up: judgment & accountability . Weakest point: trust premium .
Mixed — a routine tier and a judgment tier Sizing a tile drain lateral, running NRCS curve-number runoff models, drafting a grain bin in SolidWorks, and cleaning telemetry from soil-moisture probes are all rule-bound enough for software to carry, but nobody automates the trip out to the failing lagoon berm or the retrofit of a combine header on a specific farmer's ground — which splits the day roughly in half and puts this at 11 rather than up with field-only trades.
Some physical or field component You are on site for pump commissioning, laser grade checks, feedlot and manure pit inspections, and machinery trials in mud and dust — but that is episodic fieldwork bracketing weeks at a workstation doing hydraulic calcs and drawings, so 11 rather than the 15+ of an equipment operator who never leaves the field.
Certification preferred, not legally required The 10 reflects a real split: water-resource designs, retention structures, and grain and livestock buildings that get stamped carry PE personal liability under state engineering practice acts, while ag engineers in machinery R&D, extension, or ag-tech firms often work under the industrial exemption and never seal a drawing in their careers.
Meaningful discretion You decide design storm return periods, setback distances from wells, ventilation rates that determine whether livestock die in a heat event, and whether a lagoon liner spec is adequate under state nutrient-management rules — genuine consequential calls, but bounded by NRCS standards, ASABE specs, and permit conditions rather than made in a vacuum, which is what keeps it at 12.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (11/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (10/20) is whether the law requires a licensed human to sign. Trust premium (8/20) is whether buyers specifically pay for a person. Judgment and accountability (12/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 30 of this occupation's 52 points (58%).
Embodiment (11/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
Civil Engineers EXPOSED
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 69/100 — SAFE.
Task-mix shift as the drafting tier is absorbed: irrigation sizing, CAD, yield-data regressions and grant narratives are the automatable tier, while forensic diagnosis of why an installed drainage or manure-handling system failed — reconciling soil, contractor deviation, and operator behavior on site — is a genuinely separate tier. If firms respond by shrinking junior drafting headcount and retaining only diagnostic and commissioning roles, the remaining job is measured against harder work, though this raises the score of the surviving job while shrinking the count.
State expansion of PE-seal requirements to animal-feeding-operation waste structures: several states already require a licensed engineer's stamp on CAFO manure lagoon and containment designs under NPDES/state permit rules, but the industrial-exemption and 'NRCS-approved standard drawing' routes let much of this work proceed unstamped. If EPA's CAFO permitting revision or state ag-department rules removed the standard-drawing exemption and required a named PE to certify lagoon liner, freeboard, and storage-volume calculations — with personal liability on breach — a much larger share of the occupation's output would pass through an individual seal.
USDA NRCS conservation practice standards (Practice 313 waste storage, 590 nutrient management, 606 subsurface drain) currently allow certified technical service providers, including non-PE staff, to certify designs for cost-share payments. If NRCS restricted design certification for structural and water-resource practices above a size threshold to licensed PEs — a change already argued for by state engineering boards over TSP scope — the licensure gate would bind on funded projects, which are most projects.
State dam-safety and lagoon-failure regimes assigning a named engineer-of-record ongoing responsibility for inspection and breach risk, as North Carolina moved toward after hurricane lagoon failures. If periodic re-certification by the responsible engineer becomes the norm rather than one-time design approval, the role owns a recurring consequential call under genuine ambiguity (weather loading, aging liners) rather than a one-off deliverable.
Precision-ag and autonomous-machinery commissioning becoming a formalized field function: manufacturer and insurer requirements that autonomous tractor and sprayer deployments (e.g., John Deere autonomy, and the emerging ISO 18497 agricultural-autonomy safety standard) be validated on-site by a qualified engineer for field-boundary, obstacle, and drift conditions would attach irreducible physical presence in unpredictable terrain to the role.
The limit. No plausible route to a higher trust premium: the buyers are growers, integrators, co-ops and USDA programs purchasing a permit-satisfying deliverable at lowest cost, and there is no consumer-visible 'human-engineered' label to pay for. Also note the occupation is only ~1,480 workers; the liability levers above would raise the score of the stamping subset while doing nothing for the unstamped majority in equipment, food-process, and data roles.
| Oklahoma City, OK | 110 | $86,970 -12% |
| St. Louis, MO-IL | 100 | $124,340 +26% |
| Lafayette-West Lafayette, IN | 50 | $86,320 -12% |
| San Juan-Bayamon-Caguas, PR | 30 | $40,690 -59% |
| St. Louis, MO-IL | 100 | $124,340 +26% |
| Oklahoma City, OK | 110 | $86,970 -12% |
| Lafayette-West Lafayette, IN | 50 | $86,320 -12% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 52. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.