Lawyers

Legal

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

    0.167

    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

    0.36

    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, 60% 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 3 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
Advise clients concerning business transactions, claim liability, advisability of prosecuting or defending lawsuits, or legal rights and obligations.

O*NET Task ID 3773

0.5
Interpret laws, rulings and regulations for individuals and businesses.

O*NET Task ID 3774

0.5
Analyze the probable outcomes of cases, using knowledge of legal precedents.

O*NET Task ID 3775

0.5
Present and summarize cases to judges and juries.

O*NET Task ID 3776

0.5
Evaluate findings and develop strategies and arguments in preparation for presentation of cases.

O*NET Task ID 3777

0.5
Gather evidence to formulate defense or to initiate legal actions by such means as interviewing clients and witnesses to ascertain the facts of a case.

O*NET Task ID 3778

0.5
Examine legal data to determine advisability of defending or prosecuting lawsuit.

O*NET Task ID 3780

0.5
Present evidence to defend clients or prosecute defendants in criminal or civil litigation.

O*NET Task ID 3782

0.5
Study Constitution, statutes, decisions, regulations, and ordinances of quasi-judicial bodies to determine ramifications for cases.

O*NET Task ID 3783

0.5
Prepare legal briefs and opinions, and file appeals in state and federal courts of appeal.

O*NET Task ID 3785

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

Recent Changes Affecting This Occupation

Apr 2026: Goldman Sachs identifies lawyers as high augmentation potential from AI

[Source: Fortune/Goldman Sachs]

Apr 2026: OpenAI framework explicitly classifies lawyers (licensed, courtroom) as INSULATED — buffered by regulatory necessity (bar admission, signature liability) even when AI drafts the brief.

[Source: OpenAI Jobs Transition Framework, April 2026]

Mar 2026: Karpathy rates lawyers 9/10 for AI exposure, citing text-heavy nature of legal work as key driver.

[Source: Karpathy AI Exposure Score (Fortune)]