COOKED
The core of the job — transcribing W-2s, 1099s and receipts into tax software, picking the right forms and schedules, checking arithmetic, and e-filing — is exactly the structured document-to-form work that AI and consumer tax software already do at usable quality. A signing preparer needs a PTIN and carries penalty exposure, but PTIN registration is not a competency license, so the shield is thin compared to CPAs or Enrolled Agents. What holds is the anxious client with a messy situation — gig income, rental property, a divorce, an IRS letter — who wants a person to explain it and sign their name to it.
Dipped in 2020, then grew past where it started.
Median pay $43,080 → $54,920 +2.0% 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
+4.5%
Percentage only. The projection counts a different population from the 76,480 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 +4.5% 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.
~10,400 openings a year on average, including replacing people who leave.
Tax ExpertTax AdvisorTax PreparerTax AssociateTax EvaluatorEnrolled AgentTax AccountantTax ConsultantTax SpecialistTax ProfessionalIncome Tax ExpertIncome Tax AdvisorIncome Tax PreparerIncome Tax ConsultantCorporate Tax PreparerTax Preparer AssistantCredentialed Tax ExpertLicensed Tax ConsultantPreseason Tax ProfessionalCredentialed Tax ProfessionalCPA (Certified Public Accountant)State and Local Tax Associate (SALT Associate)
Holding it up: trust premium . Weakest point: embodiment .
Core tasks are already automatable A 1040 with a W-2, a mortgage interest 1098 and a child tax credit is a data-entry job that TurboTax has done unassisted for two decades, and OCR now pulls the boxes off a photographed 1099-NEC without you typing them — that puts the core at 4, not 10, because the residual human work is asking the client the right intake questions, not producing the return.
Fully desk- and screen-based The whole job runs from a desk with a scanner, a laptop and a client across the table or on a Zoom call; the only physical acts are handling paper receipts and shoeboxes during filing season, which is why this sits at 2 rather than 0.
Certification preferred, not legally required A PTIN costs a fee and requires no exam outside Oregon and California, and while §6694 preparer penalties and Circular 230 sanctions are real personal exposure, the taxpayer signs the return and owns the tax — that gap between 'penalizable' and 'licensed gatekeeper' is what puts this at 6 instead of an EA's 13+.
Executes defined procedures on defined inputs Most calls are bounded by the code and the software's diagnostics: filing status, dependency tests, standard versus itemized, whether a Schedule C expense is ordinary and necessary; genuinely contestable positions — basis reconstruction, hobby-loss, worker classification — usually get handed up to a CPA or EA, which keeps this at 6.
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 (4/20 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 (6/20) 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 (6/20) 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 20 of this occupation's 26 points (77%).
Embodiment (2/20) 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.
Accountants and Auditors EXPOSED
Loan Officers EXPOSED
Credit Counselors 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 45/100 — EXPOSED.
Task-mix shift: as W-2/1099 transcription and form selection are absorbed by software, the surviving billable work is genuinely two-tier — IRS notice response, audit representation, reasonable-cause penalty abatement, basis reconstruction, worker-classification and Schedule C substantiation calls. Preparers who move into representation work (which requires EA/CPA status for full practice rights) own consequential ambiguous calls.
Same two-tier shift raises task_resistance modestly: what remains is undocumented cash income, cost-basis reconstruction from missing records, multistate residency disputes, and reconciling client accounts of events that contradict the paperwork — resistant because the input is unreliable human testimony, not documents.
IRS revival of mandatory preparer competency testing and continuing education for unenrolled preparers — the Registered Tax Return Preparer regime struck down in Loving v. IRS (2014) — via the Taxpayer Protection and Preparer Proficiency Act style bill granting Treasury explicit authority. That converts PTIN registration into an actual license with revocable standing to sign returns.
State-level preparer licensing spreading beyond Oregon, California (CTEC), Maryland and New York — e.g. a new state adopting Oregon-style licensed preparer exams, plus IRS rules requiring a licensed human signature and Circular 230 diligence attestation on returns prepared with AI assistance.
IRS penalty exposure for AI-generated returns making taxpayers (or lenders/immigration filings requiring a signed preparer) demand a named human signer; also state consumer-protection actions against AI-only filing services, of the kind FTC brought against Intuit's 'free filing' claims, pushing buyers toward identified preparers.
The limit. Even with federal preparer licensing restored, the ceiling is low: the licensed tier is largely EAs and CPAs, and competency testing would likely thin the unenrolled ranks rather than protect them. Volume seasonal transcription work does not come back.
| New York-Newark-Jersey City, NY-NJ | 8,100 | $71,300 +30% |
| Los Angeles-Long Beach-Anaheim, CA | 3,250 | $65,120 +19% |
| Dallas-Fort Worth-Arlington, TX | 1,780 | $47,020 -14% |
| Phoenix-Mesa-Chandler, AZ | 1,580 | $44,770 -18% |
| San Francisco-Oakland-Fremont, CA | 1,410 | $84,240 +53% |
| Houston-Pasadena-The Woodlands, TX | 1,280 | $47,320 -14% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 1,150 | $62,010 +13% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 1,150 | $57,890 +5% |
| San Francisco-Oakland-Fremont, CA | 1,410 | $84,240 +53% |
| San Jose-Sunnyvale-Santa Clara, CA | 760 | $81,180 +48% |
| Kansas City, MO-KS | 560 | $78,920 +44% |
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 26. 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.