EXPOSED
The bulk of the day — quantity takeoffs from drawings, unit-price lookups, spreadsheet buildups, subcontractor bid leveling, and proposal write-ups — is exactly the structured document-and-numbers work that AI plan-reading and estimating platforms are absorbing fastest. What holds is the judgment layer: walking a site to see the soil, access, and existing conditions the drawings hide, pricing risk and contingency on a hard bid, and standing behind a number the company will be held to. No license protects this occupation, so the moat is credibility with owners and subs, not regulation.
Dipped in 2020, then grew past where it started.
Median pay $65,250 → $78,740 -3.5% 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
-4.2% 221,400 → 212,100 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -4.2% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.
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.
~16,900 openings a year on average, including replacing people who leave.
AnalystEstimatorCost AnalystCost EngineerJob EstimatorCost EstimatorService WriterCivil EstimatorCost ConsultantPrint EstimatorSales EstimatorService AdvisorDrywall EstimatorProject EstimatorQuantity SurveyorBuilding EstimatorConcrete EstimatorFlooring EstimatorJob Cost EstimatorPlumbing EstimatorPrinting EstimatorCommercial EstimatorElectrical EstimatorIndustrial Estimator
Holding it up: judgment & accountability . Weakest point: liability shield .
Core tasks are already automatable A 6 rather than a 10 because the sequence that fills most of an estimator's week — counting linear feet and square yards off PDF or Revit drawings, pulling RSMeans or historical unit costs, building the labor/material/equipment spreadsheet, and normalizing sub bids into a comparison sheet — is already shipped in commercial takeoff and AI plan-reading tools, leaving only site-condition interpretation and contingency setting as work that genuinely doesn't digitize.
Some physical or field component 7 covers the real but intermittent physical part: pre-bid site walks to check access, staging room, soil and existing utilities, plus occasional shop or plant visits for manufacturing estimates — but you return to a desk to actually produce the estimate, which is why this isn't a 13 like the trades you're pricing.
No licence, no signature requirement 3 because nothing legally requires a credential to estimate: CPE or CCP from AACE or ASPE helps you get hired and nothing more, and when a bid comes in low the contractor eats the loss under its own contract — no board suspends your right to practice.
Meaningful discretion 11 is where hard-bid discretion sits: you decide the escalation allowance, the productivity factor for a tight site, whether to carry a sub's suspiciously low number or self-perform, and those calls move margin by real percentages — but you recommend to a chief estimator or principal who signs the bid, so you own the analysis and not the final commitment.
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 (6/20 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 (3/20) 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 (11/20) 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 22 of this occupation's 35 points (63%).
Embodiment (7/20) 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 54/100, still EXPOSED.
Automated takeoff and unit-price lookup absorb the routine tier (already visible in Togal.AI, Autodesk Takeoff, Trimble), leaving the residual job as site-condition assessment, escalation and contingency setting on hard bids, and bid-leveling of nonconforming sub quotes. Task-mix shift, no law required — but the shift shrinks headcount even as per-worker resistance rises.
Owner or lender procurement rules requiring a named, credentialed estimator (AACE Certified Cost Professional or ASPE CPE) to seal and personally attest an independent cost estimate — the pattern already used for GAO/DOE/NASA cost-estimating standards and for some state DOT engineer's-estimate reviews. If a state DOT or FTA Capital Investment Grants condition made a named certified attestation mandatory for estimates above a threshold, the shield hardens.
Professional-liability carriers pricing design-build and GMP work on whether a human estimator of record reviewed and signed the number, and E&O policies excluding losses from unreviewed AI-generated estimates — an exclusion pattern insurers are already drafting for AI outputs. That makes the human signature a purchased item rather than a courtesy.
Growth in renovation, adaptive reuse, and infrastructure repair work — where existing conditions are undocumented and pre-bid site walks, test pits, and destructive investigation drive the number — raises the share of days that require being physically present. Federal IIJA-funded rehab of aging assets pushes this mix.
If more work shifts to hard-bid lump sum and GMP with shared-savings/overrun exposure rather than cost-plus, the estimator's contingency and escalation call becomes the direct locus of company profit or loss, and the role is formally named as estimator of record in bid documents.
The limit. No license exists and none is being drafted, so the liability lever depends entirely on private procurement or insurer terms, which are revocable and apply unevenly. Even with every lever, headcount contracts: the judgment tier needs far fewer people than the takeoff tier employed.
| New York-Newark-Jersey City, NY-NJ | 11,610 | $82,380 +5% |
| Los Angeles-Long Beach-Anaheim, CA | 7,600 | $82,260 +4% |
| Dallas-Fort Worth-Arlington, TX | 6,200 | $79,290 +1% |
| Houston-Pasadena-The Woodlands, TX | 5,660 | $78,200 -1% |
| Chicago-Naperville-Elgin, IL-IN | 4,610 | $83,640 +6% |
| Phoenix-Mesa-Chandler, AZ | 4,380 | $77,590 -1% |
| Seattle-Tacoma-Bellevue, WA | 4,340 | $94,490 +20% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 4,190 | $79,880 +1% |
| Boston-Cambridge-Newton, MA-NH | 3,110 | $102,640 +30% |
| San Francisco-Oakland-Fremont, CA | 3,300 | $101,630 +29% |
| Amherst Town-Northampton, MA | 90 | $100,410 +28% |
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 35. 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.