← Risk register SOC 11-1011 · reviewed 2026-08-11

Chief Executives

204,350 US workers · median $213,990/yr · Management

SAFE

The modal chief executive here is not a Fortune 500 CEO but the top officer of a small firm, hospital, nonprofit, or government agency — and the job is overwhelmingly negotiation, capital allocation, hiring and firing senior people, board and investor management, and owning outcomes when calls go wrong. AI already drafts the board deck, the strategy memo, the market analysis, and the earnings script, so the analytical support layer around the role thins out sharply. What does not transfer is the signature: CEOs personally certify financial statements under SOX, carry fiduciary and personal liability, and are the human counterparties boards, lenders, regulators, and key customers insist on dealing with.

10-year outlook: The role persists and its leverage rises as AI thins out the management and analyst layers beneath it, but expect fewer executives per dollar of revenue and boards demanding sharper evidence that a human, not a model, made the call.

US employment, 2019–2025-0.7%
205,890204,350 workers

Roughly flat across the period, with year-to-year wobble.

Median pay $184,460 → $213,990 -7.2% in real terms (nominal +16.0%, 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

+4.3%

Percentage only. The projection counts a different population from the 204,350 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.

Hard to automate, and growing

The work resists current AI and the BLS projects +4.3% more of these jobs by 2034. Note that safe does not mean well paid — several of the fastest-growing resistant occupations are among the lowest paid on the register.

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.

~22,200 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.

PresidentStaff ChiefAgency OwnerBureau ChiefChief WardenCommissionerBank PresidentMedia ExecutiveMusic ExecutiveTax CommissionerWelfare DirectorExecutive OfficerRoad CommissionerBusiness ExecutiveExecutive DirectorLabor CommissionerNonprofit DirectorWater CommissionerCorporate ExecutiveCounty CommissionerFoundation DirectorHealth CommissionerLiquor CommissionerPolice Commissioner

Score — 69/100 resistance

Holding it up: judgment & accountability (20/20). Weakest point: embodiment (7/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 13 + 7 + 12 + 17 + 20 = 69. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 13/20

Mixed — a routine tier and a judgment tier At 13 rather than 17, the honest split is that the memo-writing half of the job — competitive analysis, board decks, budget variance narratives, the first draft of the reorg plan — is already machine work, while the irreducible half is sitting across from a lender renegotiating a covenant, telling a division head their unit is being closed, and reading a room of skeptical trustees.

Embodiment 7/20

Some physical or field component 7 reflects that the office and the Zoom call are the default, but the job still drags you into plant walkthroughs, hospital floor rounds, site visits before an acquisition closes, and the airport-and-dinner circuit where deals actually get agreed — physical presence that is habitual but not skilled manual work.

Liability shield 12/20

Licensed human required and personally liable 12 sits above the certification band because there is no CEO licence to revoke, yet Sarbanes-Oxley 302/906 requires you to personally attest to the financials with criminal exposure, and state fiduciary duty law puts your own assets in front of derivative suits — statutory personal accountability without a credentialing body.

Trust premium 17/20

The human relationship is the product 17 because the board hired a person, not a function: lenders extend the line on your track record, the anchor customer signed because you flew out, and the succession search that replaces you takes nine months and a retained firm precisely because the relationships do not transfer with the title.

Judgment & accountability 20/20

Exists to be accountable for ambiguous calls 20 is right because nobody above you resolves the ambiguity — you decide whether to take the dilutive round or cut 15% of staff, with contradictory data and no procedure, and when it goes wrong the board fires you rather than reviewing the process.

Scored twice. An independent second run returned 68/100 — SAFE, agreeing with the verdict above.

Confidence: high · 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: judgment, liability, trust

How to future-proof this job

Where to go deeper on what this job runs on: Coursera — decision making under uncertainty free to audit · Coursera — critical thinking and logic, audit free free to audit · MIT OpenCourseWare — problem-solving and analytical method courses free · Toastmasters — public speaking practice at local clubs worldwide low · Coursera — project coordination and cross-team delivery free to audit · edX — systems thinking and evaluation methods free to audit

All 35 skills ranked by how many jobs they open →

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 80/100, still SAFE.

4 specific changes that would raise this score
  • already happening liability shield +4

    Statutory personal certification duties extending beyond SOX 302/906 financials into new domains: SEC cyber disclosure (Item 1.05) practice hardening into named-officer attestation, NYDFS Part 500 annual senior-officer certification spreading to other regulators, EU CSRD/CSDDD sustainability and human-rights due-diligence sign-off binding US parents of EU subsidiaries, and Colorado SB 24-205 / EU AI Act deployer duties requiring a named accountable officer for high-risk AI decisions. Each adds a document a human executive must personally sign under penalty.

  • already happening task resistance +3

    Task-mix shift: the analytical tier (board decks, market analysis, model-building, earnings scripts, memo drafting) automates away, leaving a residue that is almost entirely live negotiation, senior hiring and firing, and capital allocation under contested information. This raises the share of the remaining day AI cannot do at usable quality without any new law.

  • plausible liability shield +2

    D&O insurers or lenders writing covenants that void coverage where a material representation, forecast, or loan certification was generated without a named human officer's documented review — the insurer-side analogue of the sign-off requirement, enforced by contract rather than statute.

  • plausible trust premium +2

    Board and lender practice codifying human presence: NACD/institutional-investor guidance or lending-agreement terms requiring the CEO personally (not a delegate or automated system) in diligence sessions, covenant discussions, and key-customer escalation. Headroom is small because this is already near-universal informally.

The limit. judgment_accountability is already at 20 and embodiment has no route. Practical ceiling is roughly 76-78; the binding constraint is task_resistance, since the drafting and analysis layer around the role is genuinely being absorbed even as the signature and the accountability are not.

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 324 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

Los Angeles-Long Beach-Anaheim, CA 10,800 $234,290 +9%
New York-Newark-Jersey City, NY-NJ 7,180 $301,440 +41%
Boston-Cambridge-Newton, MA-NH 5,210 —
San Francisco-Oakland-Fremont, CA 5,190 $288,690 +35%
Minneapolis-St. Paul-Bloomington, MN-WI 4,500 $209,980 -2%
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 4,120 $292,770 +37%
Sacramento-Roseville-Folsom, CA 3,680 $169,770 -21%
Chicago-Naperville-Elgin, IL-IN 3,610 $344,960 +61%

Best paid

Medford, OR 40 $615,500 +188%
Midland, MI 60 $587,950 +175%
Midland, TX 100 $389,330 +82%

Percentages are against this occupation's national median of $213,990. 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 69. 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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