Software QA Analysts

Computer & Mathematical

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

    0.519

    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

    0.53

    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, 14% 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
Design test plans, scenarios, scripts, or procedures.

O*NET Task ID 14638

1.0
Test system modifications to prepare for implementation.

O*NET Task ID 14639

1.0
Develop testing programs that address areas such as database impacts, software scenarios, regression testing, negative testing, error or bug retests, or usability.

O*NET Task ID 14640

1.0
Document software defects, using a bug tracking system, and report defects to software developers.

O*NET Task ID 14641

1.0
Identify, analyze, and document problems with program function, output, online screen, or content.

O*NET Task ID 14642

1.0
Monitor bug resolution efforts and track successes.

O*NET Task ID 14643

1.0
Create or maintain databases of known test defects.

O*NET Task ID 14644

1.0
Plan test schedules or strategies in accordance with project scope or delivery dates.

O*NET Task ID 14645

1.0
Review software documentation to ensure technical accuracy, compliance, or completeness, or to mitigate risks.

O*NET Task ID 14647

1.0
Document test procedures to ensure replicability and compliance with standards.

O*NET Task ID 14648

1.0
Visit beta testing sites to evaluate software performance.

O*NET Task ID 14662

0.0
Recommend purchase of equipment to control dust, temperature, or humidity in area of system installation.

O*NET Task ID 21681

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