Will AI replace Special Education Teachers, All Other? 74/100

SAFE

This residual category covers special education teachers outside the standard preschool/elementary/middle/secondary buckets — itinerant specialists, adult transition and vocational instructors, hospital and residential program teachers. The paperwork layer (IEP drafting, progress-note narratives, accommodation checklists, lesson differentiation) is squarely in AI's wheelhouse, but the core job is physically managing behavior, delivering hand-over-hand instruction, de-escalating crises, and sitting across from families in legally consequential IEP meetings. State licensure with special education endorsement plus IDEA's procedural due-process regime keeps a named, liable human in the chair.

10-year outlook: Headcount holds or grows on rising identification rates and chronic vacancies; the documentation half of the day shrinks sharply, which mostly buys back time rather than cutting jobs.

74/100 risk resistance · ±3 on re-score

US employment, 2019–2025-4.7%

35,60033,930 workers

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

Median pay $61,190 → $76,580 +0.1% in real terms (nominal +25.2%, 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

+1.1%

Percentage only. The projection counts a different population from the 33,930 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 +1.1% 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.

~2,900 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.

TeacherAutism TutorBlind TeacherBraille TeacherInterventionistSpecial EducatorInclusion TeacherElementary TeacherReading SpecialistBehavior SpecialistLearning SpecialistLip Reading TeacherResource SpecialistHome Therapy TeacherEarly InterventionistPublic School TeacherSign Language TeacherSpecial Needs TeacherAutism Motor SpecialistAcademic InterventionistAdaptive Skills EducatorBehavior InterventionistHearing Impaired TeacherLearning Support Teacher

This is a catch-all code, not a single job

The BLS uses Special Education Teachers, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:

The score is an average over dissimilar work. Your own role could sit well above or below it, and the five dimensions describe the bucket rather than any one job inside it.
We've withheld the transfer routes here. They are computed from skill-profile overlap, and a bucket's profile is an average of unrelated jobs — which produces confident-looking matches that are meaningless. Better to show none than to point someone at the wrong career.

If a more specific occupation on the register describes what you actually do, that page is the one to trust.

Score — 74/100 resistance

Holding it up: trust premium (17/20). Weakest point: liability shield (13/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 13 + 15 + 13 + 17 + 16 = 74. · 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 IEP goal-bank drafting, progress-monitoring graphs, quarterly narrative reports and accommodation matrices are already being generated by district software, which pulls this below 14 — but the residual duties (running a discrete-trial session, prompting a student through a job-site task at a grocery store, physically blocking a self-injurious behavior) have no digital substitute, so it does not fall into the mixed-to-automatable range either.

Embodiment 15/20

Hands-on in uncontrolled environments Hand-over-hand instruction, toileting and feeding support, CPI/Safety-Care physical restraint and escort holds, and itinerant travel between school sites, hospital rooms, group homes and community job placements put this above the 13 threshold; it stops short of 18 because a meaningful share of the week is still classroom-based and in a building the employer controls.

Liability shield 13/20

Licensed human required and personally liable A state teaching licence with a special education endorsement is mandatory and revocable, and under IDEA the teacher signs as a required IEP team member whose written statements become the evidentiary record in a due-process hearing — but the district, not the teacher, is the named respondent in those hearings and carries the damages, which is why this sits at 13 rather than the 17-plus of professions where personal malpractice exposure attaches.

Trust premium 17/20

The human relationship is the product Parents of students with low-incidence disabilities follow specific teachers across grade levels and program placements, and a nonverbal student's ability to work at all often depends on one adult who has learned that student's idiosyncratic communication and behavioral triggers over months — the person is not interchangeable, which is what separates this from ordinary instructional roles.

Judgment & accountability 16/20

Exists to be accountable for ambiguous calls Calling whether a behavior is a manifestation of disability under IDEA's discipline provisions, deciding when to restrain versus clear the room, judging whether an 18-year-old is ready for supported competitive employment or a sheltered setting, and choosing which goals to abandon on a transition plan are unscripted decisions with legal and life-course consequences; it holds at 16 rather than higher because these are made in a team structure with an administrator and related-service providers signing alongside.

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

How to future-proof this job

Let AI draft IEP goals and progress narratives, then own the clinical sign-off and the meeting where those goals are defended to parents and district counsel.
Add a behavior credential (BCBA coursework or state crisis-intervention certification) to anchor to the de-escalation and functional-behavior-assessment tier that cannot be delivered on screen.
Move toward transition/vocational specialist roles — job coaching, community-based instruction, agency handoffs at 18–22 — where the work is physically in workplaces and homes.
Become the district's assistive-technology and AAC lead: assessing, fitting, and troubleshooting devices with individual students is embodied, billable, and chronically short-staffed.

Where to go deeper on what this job runs on: Coursera — teaching and instructional design, audit free free to audit · Coursera — active listening and communication skills free to audit · Toastmasters — public speaking practice at local clubs worldwide low · MIT OpenCourseWare — full course materials across every department, free free · Coursera — communication and interpersonal skills free to audit · Khan Academy — reading and vocabulary, all levels, free free

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 87/100, still SAFE.

6 specific changes that would raise this score

already happening liability shield +3

State education agencies or OSEP guidance requiring that any AI-generated IEP content (goals, present-levels narratives, accommodation lists) be reviewed and personally attested by the named case-manager holding the special education endorsement — mirroring the 2024-25 wave of state guidance (e.g. California, Ohio, Washington AI-in-education guidance) that already says AI may not author IEP decisions. A rule making that attestation a due-process defect if absent would harden it into a signature requirement.
already happening task resistance +3

Task-mix shift: this role genuinely has two tiers. If IEP drafting, progress narratives, and differentiation planning are absorbed by district-licensed tools (PowerSchool, Frontline AI features already marketed for this), the residual day is crisis de-escalation, hand-over-hand instruction, transition-site job coaching, and adversarial parent meetings — all low-substitutability.
plausible liability shield +2

Due-process hearing officers or a federal circuit holding that an IEP substantially drafted by AI without documented individualized human judgment is a procedural violation under IDEA, creating compensatory-education liability — one published decision would force districts to name and log a human author per document.
plausible embodiment +2

Caseload reallocation toward the most physically involved students — restraint/seclusion-trained itinerant staff, hospital and residential placements, feeding and toileting support — as lighter-touch consultative caseloads are consolidated with AI planning support. Also state restraint-and-seclusion laws requiring a trained, physically present licensed adult.
plausible judgment accountability +2

Formal designation as the accountable decision-maker for placement-restrictiveness and behavior-intervention-plan calls — e.g. district policy requiring the endorsed teacher, not an algorithmic risk score, to authorize a change in least-restrictive-environment placement.
plausible trust premium +1

Parent-driven insistence on a human case manager, expressed through IEP-team composition demands and advocacy groups (COPAA has already raised AI-drafted IEPs); if districts adopt contract language guaranteeing a named human case manager per student, the premium is institutionalized.

The limit. Already 74 with trust and judgment near the top; realistic headroom is in the high 70s to low 80s. The main downward pressure is not automation of the core role but funding-driven caseload expansion — one teacher covering more students with AI paperwork support, which shrinks headcount without changing the score.

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 103 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	4,230	$109,600 +43%
Baltimore-Columbia-Towson, MD	2,270	$76,090 -1%
New York-Newark-Jersey City, NY-NJ	1,880	$66,170 -14%
Chicago-Naperville-Elgin, IL-IN	1,550	$74,180 -3%
Detroit-Warren-Dearborn, MI	1,250	$79,500 +4%
Las Vegas-Henderson-North Las Vegas, NV	1,030	$64,410 -16%
Washington-Arlington-Alexandria, DC-VA-MD-WV	890	$79,880 +4%
Riverside-San Bernardino-Ontario, CA	580	$101,850 +33%

Best paid

Salinas, CA	200	$112,900 +47%
Vallejo, CA	110	$110,000 +44%
Los Angeles-Long Beach-Anaheim, CA	4,230	$109,600 +43%

Percentages are against this occupation's national median of $76,580. 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 74. 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.

Watch this verdict

Kept current

The dispatch runs daily. 711 reported cases on file, 357 of them things a named organisation actually did. Newest landed yesterday. See it · RSS
Scores move on evidence, not on a clock. Re-scoring the same occupation drifts a couple of points on its own, so a scheduled refresh would mostly republish our own noise. An occupation is re-examined when deployments accumulate against it — which is why a verdict changing here means something. Last register revision 2026-08-11.
Employment updates once a year, when the BLS publishes. Every occupation carries its own 2019–2025 series.

Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.

Cooked Index — Special Education Teachers, All Other: SAFE, 74/100.
Scored 2026-08-11 · printed from https://cookedindex.com/jobs/special-education-teachers-all-other/
Verdicts are re-examined as evidence accumulates, so this sheet goes out of date. Check the page above for the current score, the reasoning behind each dimension, and what would move it.

Special Education Teachers, All Other