EXPOSED
The document half of this job — writing curriculum maps, aligning units to state standards, building pacing guides, drafting PD slide decks, summarizing benchmark assessment data — is exactly what language models already do at usable quality, and publishers are shipping AI-generated standards-aligned materials directly to districts. What survives is the human half: sitting in a third-grade classroom watching a struggling teacher, running the follow-up coaching conversation, and owning the recommendation when a district spends $2M on a new reading program. Most coordinators hold a teaching license and many need an administrator credential, but no law requires a human signature on a curriculum document, so the credential is a hiring filter rather than a liability shield.
Headcount grew steadily across the period.
Median pay $66,290 → $77,440 -6.5% 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
+1.3% 232,600 → 235,500 on the projections basis
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +1.3% 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.
~21,900 openings a year on average, including replacing people who leave.
Course DeveloperCurriculum ManagerCurriculum DesignerCurriculum DirectorInstructional CoachLearning ConsultantLearning SpecialistLiteracy ConsultantLiteracy SpecialistCourseware DeveloperCurriculum DeveloperEducation ConsultantEducation SpecialistEducation SupervisorCurriculum SpecialistCurriculum SupervisorEducation CoordinatorInstructional ManagerProgram AdministratorCurriculum CoordinatorCurriculum FacilitatorEducational SpecialistInstructional DesignerSchool Standards Coach
Holding it up: trust premium . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Crosswalking a unit to state standards, rewriting pacing guides after a calendar change, and producing the benchmark data slides for the November leadership meeting are text-transformation jobs a model does in minutes, which drags this to 8 despite the classroom observation cycles and PD facilitation that still need a body in the room.
Some physical or field component You are in buildings — walking classrooms during observation windows, hauling materials to PD sessions, sitting at the back of a third-grade guided reading group — but it is a school, not a roof or a rig, so the physical component is scheduling and presence rather than anything a machine physically cannot do, which puts it at 7 not 13.
Certification preferred, not legally required A teaching license plus an administrator or curriculum-supervisor endorsement is standard in most states for the district-level posting, and that credentialing floor is why this is 6 rather than 2 — but no statute requires a licensed human to sign a curriculum map or adoption recommendation, so nobody's certificate is at risk when the program flops.
Meaningful discretion Recommending the $2M reading adoption and deciding which teacher needs support versus documentation are genuinely consequential calls, but they run through adoption committees, board votes, and the assistant superintendent who actually signs, so you own the analysis rather than the decision — 10, not 15.
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 (6/20) is whether the law requires a licensed human to sign. Trust premium (11/20) is whether buyers specifically pay for a person. Judgment and accountability (10/20) 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 27 of this occupation's 42 points (64%).
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.
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 66/100, still EXPOSED.
Genuine two-tier job: if publishers' AI-generated aligned materials absorb the drafting tier (maps, pacing guides, PD decks, benchmark summaries), the remaining role is classroom observation, coaching conversations with resistant or struggling teachers, and vendor evaluation — work current models cannot do at usable quality. This rises only where districts retain the coaching FTE rather than cutting the line item, which is the open question.
Accessibility liability attaching personally to the curriculum reviewer: DOJ's 2024 Title II web/ADA rule (WCAG 2.1 AA, compliance deadlines 2026-2027) plus OCR resolution agreements pushing districts to designate a specific credentialed person who certifies digital instructional materials as accessible before adoption.
A state instructional-materials review rule that names a licensed individual — not a committee — as the required signer that AI-generated or AI-assisted curriculum was reviewed for standards alignment, bias, and accessibility. Mechanisms already in motion: Texas SBOE's Instructional Materials Review and Approval (IMRA) process under HB 1605, California's SBE adoption/IMET reviews, and the wave of state 'AI in education guidance' documents (over 25 states now) that so far only recommend human review. If any of those recommendations becomes a rule requiring a named credentialed reviewer of record who can be sanctioned by the licensing board, the credential turns from hiring filter into shield.
Adoption-accountability provisions in science-of-reading and curriculum-transparency statutes that require a district to identify the individual who recommended a program and to file a written justification and post-adoption efficacy report to the state (as in some ESSA evidence-tier and Mississippi/Tennessee literacy-law reporting regimes). Owning a documented, auditable $2M call under ambiguity is exactly what raises this dimension.
Collective bargaining or state PD rules specifying that instructional coaching, classroom observation, and post-observation conferences must be conducted by a credentialed human coach and may not be delivered or scored by an automated system — parallel to existing contract language restricting video/algorithmic teacher evaluation (Chicago CTU, UTLA-type clauses) and to state bans on AI as sole evaluator. Also Title II-A spending rules being written to require human-delivered coaching hours.
A shift in the job description toward mandated in-classroom observation minimums (some state literacy-coach statutes, e.g. Florida and Mississippi coaching models, specify minimum hours of in-class modeling and observation per coach). Codified on-site hours make the role harder to run remotely or from dashboards.
The limit. Even with every lever, this occupation caps out in the low 60s. The headcount risk is budgetary, not capability-based: instructional coordinator lines are district central-office overhead, historically the first cut when ESSER-style funds expire, and no liability rule protects a position that is eliminated rather than automated. A liability shield also protects the function, not the count — one signer can certify materials for a whole district.
| New York-Newark-Jersey City, NY-NJ | 15,240 | $85,730 +11% |
| Dallas-Fort Worth-Arlington, TX | 9,080 | $80,740 +4% |
| Houston-Pasadena-The Woodlands, TX | 8,030 | $77,430 +0% |
| Chicago-Naperville-Elgin, IL-IN | 7,790 | $77,900 +1% |
| Los Angeles-Long Beach-Anaheim, CA | 7,300 | $84,850 +10% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 5,190 | $105,220 +36% |
| Atlanta-Sandy Springs-Roswell, GA | 4,660 | $81,520 +5% |
| Phoenix-Mesa-Chandler, AZ | 4,560 | $65,340 -16% |
| Napa, CA | 60 | $126,730 +64% |
| Mount Vernon-Anacortes, WA | 70 | $124,090 +60% |
| Hanford-Corcoran, CA | 30 | $115,290 +49% |
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 42. 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.