Loss Prevention Specialists

Protective Service

AI exposure

  • Data source: BLSPublished: 2026-08

    Moderate· 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

    0.057

    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

    0.20

    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, 86% 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
Maintain documentation or reports on security-related incidents or investigations.

O*NET Task ID 17567

1.0
Prepare written reports on investigations.

O*NET Task ID 17570

1.0
Implement or monitor processes to reduce property or financial losses.

O*NET Task ID 17560

0.5
Investigate known or suspected internal theft, external theft, or vendor fraud.

O*NET Task ID 17561

0.5
Collaborate with law enforcement agencies to report or investigate crimes.

O*NET Task ID 17562

0.5
Conduct store audits to identify problem areas or procedural deficiencies.

O*NET Task ID 17563

0.5
Identify and report merchandise or stock shortages.

O*NET Task ID 17565

0.5
Inspect buildings, equipment, or access points to determine security risks.

O*NET Task ID 17566

0.5
Monitor compliance with standard operating procedures for loss prevention, physical security, or risk management.

O*NET Task ID 17568

0.5
Recommend new or improved processes or equipment to reduce risk exposure.

O*NET Task ID 17571

0.5
Direct work of contract security officers or other loss prevention agents.

O*NET Task ID 17564

0.0
Perform covert surveillance of areas susceptible to loss, such loading docks, distribution centers, or warehouses.

O*NET Task ID 17569

0.0
Train establishment personnel in loss prevention activities.

O*NET Task ID 17572

0.0
Verify proper functioning of physical security systems, such as closed-circuit televisions, alarms, sensor tag systems, or locks.

O*NET Task ID 17573

0.0
Testify in civil or criminal court proceedings.

O*NET Task ID 17574

0.0
Apprehend shoplifters in accordance with guidelines.

O*NET Task ID 17575

0.0
Respond to critical incidents, such as catastrophic events, violent weather, or civil disorders.

O*NET Task ID 17580

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