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AI Automation Index
Will AI Replace Proofreaders and Copy Markers?
Task-level automation exposure for Proofreaders and Copy Markers: 11 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
75%
weighted task index
11 of 11 tasks scored
Median Salary
$51,120 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
4,580 people hold this job — size, not growth
Projected 2025–35
-0.9%
employment change
1,100 openings a year · BLS line item
Pay by state
BLS OEWS publishes 26 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$35,530 – $68,120
Highest medians
District of Columbia $68,120
New York $59,740
California $57,490
Massachusetts $57,160
New Jersey $56,700
Lowest medians
Michigan $35,530
Florida $35,610
West Virginia $36,730
Indiana $40,920
Texas $41,990
State figures come from the 43-9081 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 75%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 65%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 9%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 15/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
11 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 73%
8 tasks
Medium exposure (≥ 35%) 27%
3 tasks
Low exposure (below 35%) 0%
0 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- New 07/2016 · Incumbent
Check the facts of stories using the internet.
- New 07/2016 · Incumbent
Design page layouts using text, photographs, graphics, and other elements.
Constituent Tasks
#5159 · Core · 88% automatable
Mark copy to indicate and correct errors in type, arrangement, grammar, punctuation, or spelling, using standard printers' marks.
text generation — Proofreading text for accuracy is core LLM strength
Proofread documents, records, or other files to ensure accuracy.
#5160 · Core · 88% automatable
Read corrected copies or proofs to ensure that all corrections have been made.
text generation — Proofreading text for accuracy is core LLM strength
Proofread documents, records, or other files to ensure accuracy.
#5158 · Core · 88% automatable
Correct or record omissions, errors, or inconsistencies found.
text generation — Proofreading text for accuracy is core LLM strength
Proofread documents, records, or other files to ensure accuracy.
#5161 · Core · 85% automatable
Compare information or figures on one record against same data on other records, or with original copy, to detect errors.
data analysis — Transactional data verification is rule-based and reliable
Verify accuracy of financial or transactional data.
#5163 · Core · 45% automatable
Route proofs with marked corrections to authors, editors, typists, or typesetters for correction or reprinting.
interpersonal — Operational coordination requires live human orchestration
Coordinate operational activities.
#5162 · Core · 85% automatable
Consult reference books or secure aid of readers to check references with rules of grammar and composition.
information retrieval — Search files and references for info
Search files, databases or reference materials to obtain needed information.
#20907 · Core · 55% automatable
Consult with authors and editors regarding manuscript changes and suggestions.
interpersonal — Live collaborative negotiation of production details needs human presence
Collaborate with others to determine production details.
#20908 · Core · 65% automatable
Archive documents, conduct research, and read copy, using the internet and various computer programs.
information retrieval — Search sources for specific data is core
Search information sources to find specific data. File documents or records.
#20909 · Core · 50% automatable
Write original content, such as headlines, cutlines, captions, and cover copy.
text generation — News drafting assisted; reporting and delivery human
Report news to the public.
#20910 · Supplemental · 88% automatable
Typeset and measure dimensions, spacing, and positioning of page elements, such as copy and illustrations, to verify conformance to specifications, using printer's ruler or layout software.
text generation — Proofreading text for accuracy is core LLM strength
Proofread documents, records, or other files to ensure accuracy.
#5165 · Supplemental · 88% automatable
Read proof sheets aloud, calling out punctuation marks and spelling unusual words and proper names.
text generation — Proofreading text for accuracy is core LLM strength
Proofread documents, records, or other files to ensure accuracy.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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