Loyalty Program Managers

Sales & Marketing

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

    0.173

    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

    0.39

    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

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
Prepare budgets and submit estimates for program costs as part of campaign plan development.

O*NET Task ID 3223

0.5
Plan and prepare advertising and promotional material to increase sales of products or services, working with customers, company officials, sales departments, and advertising agencies.

O*NET Task ID 3224

0.5
Inspect layouts and advertising copy, and edit scripts, audio, video, and other promotional material for adherence to specifications.

O*NET Task ID 3226

0.5
Coordinate activities of departments, such as sales, graphic arts, media, finance, and research.

O*NET Task ID 3227

0.5
Prepare and negotiate advertising and sales contracts.

O*NET Task ID 3228

0.5
Identify and develop contacts for promotional campaigns and industry programs that meet identified buyer targets, such as dealers, distributors, or consumers.

O*NET Task ID 3229

0.5
Confer with department heads or staff to discuss topics such as contracts, selection of advertising media, or product to be advertised.

O*NET Task ID 3231

0.5
Monitor and analyze sales promotion results to determine cost effectiveness of promotion campaigns.

O*NET Task ID 3233

0.5
Read trade journals and professional literature to stay informed on trends, innovations, and changes that affect media planning.

O*NET Task ID 3234

0.5
Formulate plans to extend business with established accounts and to transact business as agent for advertising accounts.

O*NET Task ID 3235

0.5
Represent company at trade association meetings to promote products.

O*NET Task ID 3245

0.0
Attend or participate in conferences, community events, and promotional events related to products or technologies.

O*NET Task ID 21219

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