Category: Office & administrative support · SOC 43-6014.00 · Industry: Administration
Moderate exposure
3 Oct 2026
19 hours ago · sources: BLS OES (approx) · O*NET
3 sources
20 core tasks shown · 11 secondary hidden
Secretaries and Administrative Assistants, Except Legal, Medical, and Executive High exposure: 11 of 20 core tasks show high task automation potential : exposure 59/100 (moderate exposure).
No model has published evidence mapped to this occupation yet - the score comes from generic task assessment.
Score breakdown
Every component is stored with the score row and can be recomputed from the evidence table.
Methodology 2026-09-a · score v1.0 · input hash a09c39c89b93d13a
Strength of current models on the capabilities this job's tasks require.
Task-level exposure, weighted by task importance. A component of the headline, not the headline itself.
Evidence that AI is actually being used for this work.
Observed changes in postings, employment or earnings.
Quantity and source quality of the evidence behind the score.
3 evidence item(s) contribute. Calculated 19 hours ago. 3 Oct 2026 UTC.
Perform routine administrative functions such as drafting correspondence, scheduling appointments, organizing and maintaining paper and electronic files, or providing information to callers.
Employment
≈1,900,000
approx. BLS OES
Median wage
≈$46,000
approx. BLS OES
Tasks tracked
31
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
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.
core task · importance 4.3/5
core task · importance 4.3/5
core task · importance 4.2/5
core task · importance 4.2/5
core task · importance 4.1/5
core task · importance 4/5
core task · importance 4/5
core task · importance 3.9/5
core task · importance 3.8/5
core task · importance 3.8/5
core task · importance 3.8/5
core task · importance 3.7/5
core task · importance 3.7/5
core task · importance 3.7/5
core task · importance 3.7/5
core task · importance 3.7/5
core task · importance 3.5/5
core task · importance 3.4/5
core task · importance 3.3/5
core task · importance 3.3/5
Evidence
3 attributed item(s). Confidence reflects study design: randomised and production deployments score higher than platform observations, which score higher than projections.
Using O*NET task descriptions scored by GPT-4, the authors estimate that about 80% of the US workforce could have at least 10% of their tasks affected by large language models, and about 19% could see at least 50% of their tasks affected.
This is a *capability and exposure* estimate produced by having a model rate task descriptions — not a measurement of employment change. It is the most-cited exposure figure in the field and is included here as an exposure input, weighted accordingly.
Source: Eloundou, Manning, Mishkin & Rock — GPTs are GPTs (arXiv:2303.10130) · Updated 24 Aug 2023
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
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
Backcast series: recomputed at quarterly checkpoints using only the models and evidence published by each date.
Reconstruction, not measurement. 5 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
BLS ten-year employment projections list data entry keyers and closely related clerical occupations among the occupations with the largest projected employment declines.
Using O*NET task descriptions scored by GPT-4, the authors estimate that about 80% of the US workforce could have at least 10% of their tasks affected by large language models, and about 19% could see at least 50% of their tasks affected.
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.
Related
Occupations sharing major SOC group (43) with Secretaries and Administrative Assistants, Except Legal, Medical, and Executive.
faq
Common questions regarding Secretaries and Administrative Assistants, Except Legal, Medical, and Executive and AI exposure.
Current AI models show an exposure score of 59/100 for Secretaries and Administrative Assistants, Except Legal, Medical, and Executive. This measures technical capability to assist or automate specific tasks rather than predicted immediate job loss. Moderate exposure reflects assistance in routine information-handling while core responsibilities require human judgment.
The most exposed tasks for Secretaries and Administrative Assistants, Except Legal, Medical, and Executive include "Schedule and confirm appointments for clients, customers, or supervisors." (85% exposure) and "Complete forms in accordance with company procedures." (85% exposure).
Tasks with the lowest AI exposure for Secretaries and Administrative Assistants, Except Legal, Medical, and Executive include "Make copies of correspondence or other printed material." (10% exposure) and "Operate office equipment, such as fax machines, copiers, or phone systems and arrange for repairs when equipment malfun…" (10% exposure). These responsibilities typically require physical dexterity, licensed human accountability, or complex interpersonal navigation.
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Notice: All ratings shown are AI-estimated technical exposure scores measuring technical capabilities across O*NET task statements, not predicted job loss. Contains information from O*NET 31.0 by the U.S. Department of Labor, ETA, used under CC BY 4.0.