Vocational Education Teachers

Education & Training

AI exposure

  • Data source: BLSPublished: 2026-08

    Very high· relative

    LowFour relative bandsVery high

    Group-level value

    Scale, basis and source

    Four relative bands (Low / Moderate / High / Very high)

    831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.156

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.35

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 61% score at or above this value.

    Source dataset

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

Task-level exposure

Exposed tasks only

Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

TaskβE1 + 0.5 × E2
Prepare reports and maintain records, such as student grades, attendance rolls, and training activity details.

O*NET Task ID 6449

1.0
Prepare outlines of instructional programs and training schedules and establish course goals.

O*NET Task ID 6455

1.0
Review enrollment applications and correspond with applicants to obtain additional information.

O*NET Task ID 6462

1.0
Observe and evaluate students' work to determine progress, provide feedback, and make suggestions for improvement.

O*NET Task ID 6446

0.5
Present lectures and conduct discussions to increase students' knowledge and competence using visual aids, such as graphs, charts, videotapes, and slides.

O*NET Task ID 6447

0.5
Administer oral, written, or performance tests to measure progress and to evaluate training effectiveness.

O*NET Task ID 6448

0.5
Supervise independent or group projects, field placements, laboratory work, or other training.

O*NET Task ID 6450

0.5
Determine training needs of students or workers.

O*NET Task ID 6451

0.5
Provide individualized instruction and tutorial or remedial instruction.

O*NET Task ID 6452

0.5
Develop curricula and plan course content and methods of instruction.

O*NET Task ID 6454

0.5
Supervise and monitor students' use of tools and equipment.

O*NET Task ID 6445

0.0
Conduct on-the-job training classes or training sessions to teach and demonstrate principles, techniques, procedures, or methods of designated subjects.

O*NET Task ID 6453

0.0
Acquire, maintain, and repair laboratory equipment and tools.

O*NET Task ID 20106

0.0

β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.

Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information