Will AI replace Career/Technical Education Teachers, Postsecondary?
Work in Career/Technical Education Teachers, Postsecondary sits in the in-between: AI reaches some of it (~49% in theory) but is only measured doing about 16% today — part human, part machine.
O*NET-SOC 25-1194
How your 19 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~49%). By late 2025, real-world AI use had reached about 16% of its task activity (growing but still limited). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~49%), real-world use (~16%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 19 tasks, ratedBased on real task-level AI scores — click to collapse
- Prepare reports and maintain records, such as student grades, attendance rolls, and training activity details.
- Prepare outlines of instructional programs and training schedules and establish course goals.
- Observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement.
- Present lectures and conduct discussions to increase students' knowledge and competence using visual aids, such as graphs, charts, videotapes, and slides.
- Administer oral, written, or performance tests to measure progress and to evaluate training effectiveness.
- Provide individualized instruction and tutorial or remedial instruction.
- Develop curricula and plan course content and methods of instruction.
- Determine training needs of students or workers.
- Supervise independent or group projects, field placements, laboratory work, or other training.
- Integrate academic and vocational curricula so that students can obtain a variety of skills.
- Select and assemble books, materials, supplies, and equipment for training, courses, or projects.
- Advise students on course selection, career decisions, and other academic and vocational concerns.
- Participate in conferences, seminars, and training sessions to keep abreast of developments in the field, and integrate relevant information into training programs.
- Develop teaching aids, such as instructional software, multimedia visual aids, or study materials.
- Serve on faculty and school committees concerned with budgeting, curriculum revision, and course and diploma requirements.
- Arrange for lectures by experts in designated fields.
- Supervise and monitor students' use of tools and equipment.
- Conduct on-the-job training classes or training sessions to teach and demonstrate principles, techniques, procedures, or methods of designated subjects.
- Acquire, maintain, and repair laboratory equipment and tools.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.