Financial Compliance Officers

Business & Financial Operations

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

    0.121

    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

    0.43

    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, 30% 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 7 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
Prepare, organize, and maintain inspection records.

O*NET Task ID 10831

1.0
Prepare written, oral, tabular, and graphic reports summarizing requirements and regulations, including enforcement and chain of custody documentation.

O*NET Task ID 10833

1.0
Evaluate label information for accuracy and conformance to regulatory requirements.

O*NET Task ID 10844

1.0
Respond to questions and inquiries, such as those concerning service charges and capacity fees, or refer them to supervisors.

O*NET Task ID 10853

1.0
Prepare data to calculate sewer service charges and capacity fees.

O*NET Task ID 20473

1.0
Determine the nature of code violations and actions to be taken, and issue written notices of violation, participating in enforcement hearings, as necessary.

O*NET Task ID 10829

0.5
Examine permits, licenses, applications, and records to ensure compliance with licensing requirements.

O*NET Task ID 10830

0.5
Monitor follow-up actions in cases where violations were found, and review compliance monitoring reports.

O*NET Task ID 10834

0.5
Investigate complaints and suspected violations regarding illegal dumping, pollution, pesticides, product quality, or labeling laws.

O*NET Task ID 10835

0.5
Inform individuals and groups of pollution control regulations and inspection findings, and explain how problems can be corrected.

O*NET Task ID 10837

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