EXPOSED
The bread-and-butter deliverables — survey instrument drafting, job analysis write-ups, competency models, engagement report summaries, literature reviews, and standard psychometric runs — are exactly the text-and-statistics work current AI does at usable quality. What holds is the part where a named expert stands behind a selection system in an EEOC adverse-impact challenge, facilitates a leadership team through a restructuring they don't want, and decides which construct actually predicts performance in this specific job. Licensure rarely binds I-O practice (unlike clinical psychology), so the shield is thin; the moat is client trust and expert-witness-grade accountability, not regulation.
Dipped in 2020, then grew past where it started.
Median pay $92,880 → $193,950 +67.1% 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
+6.3%
Percentage only. The projection counts a different population from the 790 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +6.3% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
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.
~400 openings a year on average, including replacing people who leave.
PsychologistPolicy AdvisorPolicy OfficerResearch ScientistStaffing ConsultantTraining SpecialistManagement ConsultantPersonnel PsychologistConsulting PsychologistIndustrial PsychologistManagement PsychologistEngineering PsychologistOccupational PsychologistOrganizational ConsultantOrganizational PsychologistPersonnel Research PsychologistOrganizational Research ConsultantHR Consultant (Human Resources Consultant)HR Psychologist (Human Resources Psychologist)Organizational Development Analyst (OD Analyst)Organizational Development Consultant (OD Consultant)Organizational Development Specialist (OD Specialist)I-O Practitioner (Industrial-Organizational Practitioner)I-O Psychologist (Industrial-Organizational Psychologist)
Holding it up: trust premium . Weakest point: embodiment .
Mixed — a routine tier and a judgment tier An 8 reflects that item-writing, factor analyses, validation tables, and 360-feedback narrative reports — the volume work billed by the hour — now come out of a model in minutes, while the residual defensible core is narrower: running a live focus group with unionized supervisors, deciding whether a criterion measure is contaminated, and defending a cut score under Uniform Guidelines scrutiny.
Fully desk- and screen-based A 4 is for the occasional on-site visit — observing assembly line tasks for a job analysis, sitting in on an assessment center as an assessor — inside client offices and plants where the physical demand is walking and watching, not handling anything.
Certification preferred, not legally required At 5, the psychologist title is protected in many states and SIOP/ABPP credentials carry weight with sophisticated buyers, but I-O consulting to organizations is not a licensed act of practice, so a firm can staff a validation study with unlicensed master's-level analysts and nothing stops it.
Meaningful discretion 12 is earned by calls like whether an integrity test's adverse impact is justified by business necessity, whether to tell the CEO their pet competency model is unvalidated, and how to sequence a restructuring communication — high-consequence but usually advisory, with the client executive owning the decision and the legal exposure.
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 (8/20 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 (5/20) is whether the law requires a licensed human to sign. Trust premium (12/20) 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 29 of this occupation's 41 points (71%).
Embodiment (4/20) 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.
No occupation passed every test: close enough to industrial-organizational psychologists on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:
That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.
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 62/100, still EXPOSED.
Courts continuing to treat the Uniform Guidelines on Employee Selection Procedures (29 CFR 1607) validation record as requiring identified expert authorship — e.g. Daubert exclusion of an AI-generated validation study with no qualified human sponsor, as in EEOC v. iTutorGroup-style enforcement or the Mobley v. Workday litigation. Each such ruling makes the human signature non-optional in defensible selection systems.
Genuine two-tier structure: if survey drafting, competency-model boilerplate, and standard psychometric runs are fully absorbed by tooling, the residual role is construct choice, criterion definition, adverse-impact strategy, and defending methodology under cross-examination — work that cannot be scored from a corpus because it depends on undisclosed client facts and litigation posture. Watch for consultancy staffing shifting to senior-only I-O rosters with no junior analyst tier.
AI hiring-tool audit mandates that name a qualified assessment professional as the signing auditor: NYC Local Law 144 already requires annual independent bias audits of automated employment decision tools, and Illinois HB 3773 (effective 2026) plus Colorado SB 24-205 create adjacent duties. If a state board or EEOC guidance specifies that the validation/adverse-impact audit must be attested by a named I-O psychologist or SIOP-credentialed practitioner with personal liability, the shield moves from 'thin' to binding.
If AI-driven selection tools become the default and organizations need a human owner of the go/no-go call on deploying a scored model — analogous to the model-risk 'accountable executive' under SR 11-7 in banking — the I-O psychologist becomes the named validity owner for a system that decides employment. Watch for enterprise AI governance charters that name an assessment scientist as approver.
Employee-facing work where AI attribution destroys the product: engagement diagnostics and restructuring facilitation depend on employees believing a human, not the employer's model, read their comments. If works councils or union contracts (already common in German co-determination and appearing in some US organizing agreements) specify a human third-party interpreter of employee survey data, the premium is contractual rather than sentimental.
The limit. Very small occupation (790 workers) with most economically similar work done under other titles (HR analytics, management consulting), so title-level protections generalize poorly. Licensure is the big absent lever and unlikely: state psychology boards have historically exempted organizational consulting from practice acts, and SIOP has not pursued a practice monopoly. Without that, ceiling is roughly mid-50s.
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 41. 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.