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A/KAI Kills What?

Dossier #18 // career autopsy

Lower exposure

Data Entry Keyers

Category: Office & administrative support · SOC 43-9021.00 · Industry: Administration

AI Exposure

29/100
0.0

Low exposure

Last updated

12 Oct 2026

19 hours ago · sources: BLS OES (approx) · O*NET

Evidence

4 sources

5 core tasks shown · 4 secondary hidden

Verdict

Data Entry Keyers Lower exposure: only 3 of 5 core tasks show high task automation potential : exposure 29/100 (low exposure).

1 model with published evidence against this job. Strongest: Llama 3.1 405B (84/100 capability).

Share this verdict:

Score breakdown

Why this score?

Every component is stored with the score row and can be recomputed from the evidence table.

AI Exposure (composite)29/100

Methodology 2026-09-a · score v1.0 · input hash 13a7c24e85e8e027

AI capability exposure0/100

Strength of current models on the capabilities this job's tasks require.

Task automation potential57/100

Task-level exposure, weighted by task importance. A component of the headline, not the headline itself.

Observed AI adoption0/100

Evidence that AI is actually being used for this work.

Labour-market signal60/100

Observed changes in postings, employment or earnings.

Evidence strength59/100

Quantity and source quality of the evidence behind the score.

4 evidence item(s) contribute. Calculated 19 hours ago. 12 Oct 2026 UTC.

Overview

Operate data entry device, such as keyboard or photo composing perforator. Duties may include verifying data and preparing materials for printing.

Employment

≈150,000

approx. BLS OES

Median wage

≈$37,000

approx. BLS OES

Tasks tracked

9

linked to this occupation

Employment and wage values are approximate reference figures from the BLS Occupational Employment and Wage Statistics programme, stored with an approximation flag. Verify against the O*NET record and BLS before quoting them.

Tasks

Task-level automation exposure

All tasks →

Core tasks only. Exposure describes how much of the task output current AI can produce or substantially assist - not whether the task disappears. Secondary shared-baseline edges are hidden until per-occupation curation is complete.

Killers

Which models affect this job most

Ranked by strongest demonstrated capability. Task and evidence counts come from the attributed evidence trail below.

  1. 01
    Llama 3.1 405B84/100

    Meta · 1 evidence item

Evidence

Evidence trail

4 attributed item(s). Confidence reflects study design: randomised and production deployments score higher than platform observations, which score higher than projections.

  1. model releaseincreasesconfidence 88/100 · magnitude 4623 Jul 2024

    Llama 3.1 405B and subsequent open-weight releases let organisations run near-frontier models on their own infrastructure, changing the cost and compliance barriers to automation.

    A cost-and-adoption enabler rather than a capability jump. Included because cost is one of the main reasons high capability does not translate into adoption.

    model: Llama 3.1 405B

    Source: Meta AI · Updated 23 Jul 2024

  2. labor marketincreasesconfidence 76/100 · magnitude 5829 Aug 2024

    BLS ten-year employment projections list data entry keyers and closely related clerical occupations among the occupations with the largest projected employment declines.

    Projections are produced from structural trends including technology, demographics and demand; they are not AI-specific and not measurements. Exact series values are available from the source.

    Source: BLS Employment Projections · Updated 29 Aug 2024

  3. labor marketincreasesconfidence 74/100 · magnitude 627 Mar 2024

    Using platform data from a large online labour market, the authors find that after ChatGPT's release, jobs more exposed to AI automation experienced a relative decline in the number of projects and in freelancer earnings compared with less-exposed jobs.

    One of the few *observational labour-market outcome* studies. It is platform-specific, covers remote freelance work only, and cannot separate AI substitution from other demand shifts. Treated here as a genuine labour-market signal with medium confidence.

    Source: Hui, Reshef & Zhou — The Short-Term Effects of Generative AI on Online Labour Markets · Updated 7 Mar 2024

  4. researchincreasesconfidence 55/100 · magnitude 4826 Mar 2023

    The analysis estimates that a substantial share of current work tasks could be automated by generative AI, with a headline estimate of around 300 million full-time jobs globally exposed, and finds that most exposed occupations are partially rather than fully exposed.

    Widely quoted and widely misread. It is a task-exposure scenario, not a forecast of unemployment. Used here at low-to-medium weight, and only for the exposure discussion, not for occupation-level scoring.

    Source: Goldman Sachs Global Investment Research — The Potentially Large Effects of AI on Economic Growth · Updated 26 Mar 2023

Historical trend

Exposure over time

Backcast series: recomputed at quarterly checkpoints using only the models and evidence published by each date.

Data Entry Keyers AI exposure backcast, quarterly from 2021Reconstructed exposure series with 23 checkpoints. Current value 29 out of 100. 14 observed snapshots recorded since tracking began.1000502021-01-012026-07-010146
Score · 23 points · 2021-01-01 to 2026-07-01

Reconstruction, not measurement. 14 observed daily snapshot(s) exist for this occupation; the earlier part of the curve is derived by applying the current methodology to the model releases and published evidence available at each past date.

Recent events

Signals affecting this occupation

  1. Occupation score change
    IMPACT 100

    data entry keyer exposure decreased 31.0 points

    AI Exposure Score moved from a previous calculation to 29/100 under methodology v1.0. 4 evidence item(s) contributed.

    Verified signalConfidence:60 · moderateVerified by AIKillsWhat
  2. Occupation score change
    IMPACT 10

    data entry keyer exposure decreased 1.0 points

    AI Exposure Score moved from a previous calculation to 60/100 under methodology v1.0. 4 evidence item(s) contributed.

    Verified signalConfidence:60 · moderateVerified by AIKillsWhat
  3. Labour market update
    IMPACT 58

    Data entry occupations are already among the fastest-declining projections

    BLS ten-year employment projections list data entry keyers and closely related clerical occupations among the occupations with the largest projected employment declines.

    Workforce dataConfidence:76 · moderateVerified by AIKillsWhat
  4. New model
    IMPACT 46

    Open-weight frontier-class models enabled self-hosted automation

    Llama 3.1 405B and subsequent open-weight releases let organisations run near-frontier models on their own infrastructure, changing the cost and compliance barriers to automation.

    Frontier releaseConfidence:88 · highVerified by AIKillsWhat
  5. Labour market update
    IMPACT 62

    Automation-prone freelance work saw fewer projects and lower earnings after ChatGPT

    Using platform data from a large online labour market, the authors find that after ChatGPT's release, jobs more exposed to AI automation experienced a relative decline in the number of projects and in freelancer earnings compared with less-exposed jobs.

    Workforce dataConfidence:74 · moderateVerified by AIKillsWhat
  6. Research published
    IMPACT 48

    Estimate: about 300 million full-time jobs exposed to automation from generative AI

    The analysis estimates that a substantial share of current work tasks could be automated by generative AI, with a headline estimate of around 300 million full-time jobs globally exposed, and finds that most exposed occupations are partially rather than fully exposed.

    Labor researchConfidence:55 · lowVerified by AIKillsWhat

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