Labor Relations Specialists
LegalAI exposure
- Data source: BLSPublished: 2026-08
High· relative
LowFour relative bandsVery highGroup-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
- Data source: AnthropicPublished: 2026-03
0.000
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.45
0.09Range of values carried here0.70Group-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, 25% score at or above this value.
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 23 hidden tasks| Task | Claude.aiRaw / share % |
|---|---|
Prepare reports or presentations to communicate employee satisfaction or related data to management.13-1075 | 0.021271.0 |
Interpret contractual agreements for employers and employees engaged in collective bargaining or other labor relations processes.13-1075 | 0.00258.3 |
Advise management on matters related to the administration of contracts or employee discipline or grievance procedures.13-1075 | 0.00227.2 |
Research case law or outcomes of previous case hearings.13-1075 | 0.00216.9 |
Develop methods to monitor employee satisfaction with policies or working conditions, including grievance or complaint procedures.13-1075 | 0.00206.6 |
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.
| Task | βE1 + 0.5 × E2 |
|---|---|
Draft contract proposals or counter-proposals for collective bargaining or other labor negotiations.O*NET Task ID 18879 | 1.0 |
Draft rules or regulations to govern collective bargaining activities in collaboration with company, government, or employee representatives.O*NET Task ID 18880 | 1.0 |
Interpret contractual agreements for employers and employees engaged in collective bargaining or other labor relations processes.O*NET Task ID 18882 | 1.0 |
Prepare and submit required governmental reports or forms related to labor relations matters, such as equal employment opportunity (EEO) forms, new hire forms, or minority compensation reports.O*NET Task ID 18887 | 1.0 |
Write letters related to labor relations activities, such as letters to amend collective bargaining agreements, letters of dispute or conciliation, or letters to seek clarification of contract terms.O*NET Task ID 18895 | 1.0 |
Advise management on matters related to the administration of contracts or employee discipline or grievance procedures.O*NET Task ID 18877 | 0.5 |
Identify alternatives to proposals of unions, employees, companies, or government agencies.O*NET Task ID 18881 | 0.5 |
Investigate and evaluate union complaints or arguments to determine viability.O*NET Task ID 18883 | 0.5 |
Mediate discussions between employer and employee representatives in attempt to reconcile differences.O*NET Task ID 18884 | 0.5 |
Monitor company or workforce adherence to labor agreements.O*NET Task ID 18885 | 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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page