Instructional Coordinators

Education & Training

AI exposure

  • Data source: BLSPublished: '26.08

    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: '26.03

    0.304

    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: '25

    0.39

    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, 44% 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

Show 4 hidden tasks

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
Interpret and enforce provisions of state education codes and rules and regulations of state education boards.

O*NET Task ID 6867

1.0
Prepare or approve manuals, guidelines, and reports on state educational policies and practices for distribution to school districts.

O*NET Task ID 6878

1.0
Define instructional, learning, or performance objectives.

O*NET Task ID 22441

1.0
Develop instructional materials, such as lesson plans, handouts, or examinations.

O*NET Task ID 22444

1.0
Develop master course documentation or manuals according to applicable accreditation, certification, or other requirements.

O*NET Task ID 22445

1.0
Edit instructional materials, such as books, simulation exercises, lesson plans, instructor guides, and tests.

O*NET Task ID 22447

1.0
Advise teaching and administrative staff in curriculum development, use of materials and equipment, and implementation of state and federal programs and procedures.

O*NET Task ID 6865

0.5
Recommend, order, or authorize purchase of instructional materials, supplies, equipment, and visual aids designed to meet student educational needs and district standards.

O*NET Task ID 6866

0.5
Research, evaluate, and prepare recommendations on curricula, instructional methods, and materials for school systems.

O*NET Task ID 6870

0.5
Prepare grant proposals, budgets, and program policies and goals or assist in their preparation.

O*NET Task ID 6873

0.5

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