← Risk register SOC 13-1075 · reviewed 2026-08-11

Labor Relations Specialists

64,810 US workers · median $95,420/yr · Business

EXPOSED

A large share of the job is document work AI already handles well: parsing collective bargaining agreements, drafting grievance responses, summarizing arbitration precedent, tracking wage and benefit comparables, and writing policy language. What does not automate is sitting across a table from a union bargaining committee, reading the room during a strike threat, and owning the concession you just made. The modal worker splits time between contract administration (exposed) and live negotiation and grievance handling (durable), and headcount pressure will land on the administration half.

10-year outlook: Expect the contract-administration workload to compress sharply while a smaller cohort of negotiators, arbitration advocates, and strike-risk advisors keeps or grows its value.

US employment, 2019–2025-14.2%
75,58064,810 workers

This fall is concentrated in 2020 and has not recovered since.

Median pay $69,020 → $95,420 +10.6% in real terms (nominal +38.2%, less ~25% US inflation over the period)

The job count is not the verdict

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

-0.1% 65,400 → 65,400 on the projections basis

Exposed, and shrinking

Both signals point the same way: the tasks are largely automatable and the BLS projects -0.1% 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.

~5,100 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

ConciliatorUnion StewardBusiness AgentLabor MediatorLabor OrganizerUnion OrganizerLabor SpecialistGrievance ManagerLabor ConciliatorContract NegotiatorPersonnel ArbitratorPersonnel NegotiatorRelations SpecialistArbitration SpecialistLabor Contract AnalystLabor Relations WorkerBusiness RepresentativeLabor Relations AnalystEmployee Relations PartnerLabor Relations ConsultantLabor Relations NegotiatorLabor Relations SpecialistIndustrial Relations WorkerIndustrial Relations Analyst

Score — 43/100 resistance

Holding it up: trust premium (13/20). Weakest point: liability shield (3/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 9 + 5 + 3 + 13 + 13 = 43. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 9/20

Mixed — a routine tier and a judgment tier At 9, the split is real: the contract-interpretation memos, Article-by-Article redlines, grievance logs, and NLRB filing prep that fill most weeks are text-in/text-out work a model does competently, while the actual table sessions, caucus strategy, and Weingarten-rights investigatory interviews stay human — which is why this sits at 9 rather than the 4 of a pure document analyst or the 15 of a chief negotiator who does nothing but bargain.

Embodiment 5/20

Some physical or field component The 5 reflects that you are not on a screen exclusively — you are in plant break rooms for grievance step meetings, walking the floor to see the disputed job assignment, and in hotel conference rooms for multi-day bargaining — but nothing you touch requires manual skill or exposes you to an uncontrolled site, so it lands just above desk-only rather than in the field band.

Liability shield 3/20

No licence, no signature requirement A 3 is correct because nothing in the LMRA or NLRA requires you to hold a licence: SHRM-CP or the LRP credential is resume decoration, unfair labor practice charges are filed against the employer as a legal entity, and when a settlement goes wrong it is the company's outside labor counsel — a member of the bar — who carries the professional exposure, not you.

Trust premium 13/20

The human relationship is the product 13 recognizes that your value to management is largely the standing relationship with a specific union business agent — the off-the-record call that kills a grievance before Step 3, the credibility that lets you say "this is my last number" and be believed — but it is capped there because that relationship is with a counterparty who is institutionally adversarial and rotates with union elections, unlike a therapist's or a wealth advisor's book.

Judgment & accountability 13/20

Meaningful discretion 13 fits because you decide unilaterally whether to settle a discharge grievance or take it to arbitration, what the employer's opening economic package is, and whether conduct crosses into a Section 8(a)(5) refusal to bargain — genuinely consequential ambiguous calls — but the final ratification, the strike authorization, and the litigate-or-settle decision go up to a VP or general counsel, keeping you below the band reserved for people whose signature is the last one.

Confidence: medium · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: trust, judgment

How to future-proof this job

Training paths for your skill gaps: Learning How to Learn — the most-taken course on Coursera, and free free to audit · Coursera — teaching and instructional design, audit free free to audit · Khan Academy — physics, chemistry and biology from the ground up free · MIT OpenCourseWare — full course materials across every department, free free

All 35 skills ranked by how many jobs they open →

Where this experience transfers — occupations you could move toward

Computed from U.S. Dept. of Labor O*NET skill and knowledge profiles: high overlap with what you already do, a materially higher resistance score, no large jump in required training, and no licence you would have to start a new pipeline to get. Targets that pay meaningfully less, that are themselves COOKED, or whose own headcount is falling are excluded — a move into a shrinking trade is not an escape.

Law Teachers, Postsecondary EXPOSED · 59/100 · you already have ~70% of the skill profile

Skills to close: Learning Strategies, Instructing, Science, Active Learning

What would move this back up — beyond any one person

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 57/100, still EXPOSED.

4 specific changes that would raise this score
  • already happening task resistance +4

    Task-mix shift: if contract administration (CBA parsing, comparables tracking, grievance drafting, policy language) is absorbed by AI, the surviving role is live bargaining, strike contingency, and grievance settlement authority — genuinely two-tier work, so the residual job is the judgment tier even as headcount falls

  • plausible trust premium +4

    If national unions adopt bargaining-table policies refusing to negotiate against AI-generated proposals or AI-present sessions — the WGA/SAG-AFTRA 2023 AI clauses and the Teamsters' contract language on automation are the template — employers must staff a named human negotiator regardless of cost

  • plausible judgment accountability +3

    If NLRB or arbitrators treat unattributed AI-drafted bargaining communications as evidence of bad-faith or surface bargaining under NLRA 8(a)(5), a named human must own each proposal and concession on the record

  • unlikely liability shield +3

    If duty-of-fair-representation suits or state public-sector labor boards (e.g. PERB rules) require a designated human agent of record for grievance dispositions and interest arbitration filings, with personal exposure for the disposition

The limit. No license exists for this occupation and none is being proposed, so liability_shield has a low ceiling; the realistic path is a smaller, more senior negotiation-only role rather than a protected one.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 192 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

New York-Newark-Jersey City, NY-NJ 6,930 $107,470 +13%
Los Angeles-Long Beach-Anaheim, CA 3,300 $102,980 +8%
Chicago-Naperville-Elgin, IL-IN 3,090 $103,570 +9%
San Francisco-Oakland-Fremont, CA 2,000 $124,400 +30%
Seattle-Tacoma-Bellevue, WA 1,990 $119,200 +25%
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 1,730 $99,840 +5%
Minneapolis-St. Paul-Bloomington, MN-WI 1,300 $101,270 +6%
Boston-Cambridge-Newton, MA-NH 1,280 $118,520 +24%

Best paid

San Jose-Sunnyvale-Santa Clara, CA 510 $133,270 +40%
Vallejo, CA 100 $131,680 +38%
Santa Cruz-Watsonville, CA 40 $128,320 +34%

Percentages are against this occupation's national median of $95,420. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

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 43. 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.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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Kept current

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