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AI Automation Index
Task-level automation exposure for Correspondence Clerks: 17 O*NET tasks scored against their work activities, plus the simulator.
Automation Exposure
17 of 17 tasks scored
Median Salary
BLS OEWS, May 2025 — this exact occupation
Employment Level
4,290 people hold this job — size, not growth
Projected 2025–35
500 openings a year · BLS line item
BLS OEWS publishes 26 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$36,790 – $61,310
Highest medians
Lowest medians
State figures come from the 43-4021 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
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.
Importance-weighted mean of the scored tasks. This is the headline index.
Share of weighted tasks in hands-on or machine-operating work activities.
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Share in documenting, recording, and administrative activities.
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
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.
17 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
12 tasks
1 tasks
4 tasks
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 →Maintain files and control records to show correspondence activities.
data analysis — Maintain operational records in structured systems
Read incoming correspondence to ascertain nature of writers' concerns and to determine disposition of correspondence.
text generation — Reading and deriving actions from text is core LLM
Gather records pertinent to specific problems, review them for completeness and accuracy, and attach records to correspondence as necessary.
data analysis — Detecting recording errors is deterministic pattern matching
Prepare documents and correspondence, such as damage claims, credit and billing inquiries, invoices, and service complaints.
text generation — Routine business correspondence fully draftable by AI
Compile data from records to prepare periodic reports.
data analysis — Compiling data or documentation is largely automatable
Compose letters in reply to correspondence concerning such items as requests for merchandise, damage claims, credit information requests, delinquent accounts, incorrect billing, or unsatisfactory service.
text generation — Routine business correspondence fully draftable by AI
Route correspondence to other departments for reply.
physical manipulation — Routing physical mail requires sorting by hand
Ensure that money collected is properly recorded and secured.
physical manipulation — Preparing physical cash for deposit is hands-on
Process orders for goods requested in correspondence.
physical manipulation — Manual packing for shipping
Present clear and concise explanations of governing rules and regulations.
information retrieval — AI explains policies; human handles live questions
Review correspondence for format and typographical accuracy, assemble the information into a prescribed form with the correct number of copies, and submit it to an authorized official for signature.
text generation — Proofreading text for accuracy is core LLM strength
Compute costs of records furnished to requesters, and write letters to obtain payment.
data analysis — Cost calculation from structured inputs
Compile data pertinent to manufacture of special products for customers.
data analysis — Compiling data or documentation is largely automatable
Type acknowledgment letters to persons sending correspondence.
text generation — Routine business correspondence fully draftable by AI
Complete form letters in response to requests or problems identified by correspondence.
text generation — Routine business correspondence fully draftable by AI
Confer with company personnel regarding feasibility of complying with writers' requests.
interpersonal — Real-time coworker coordination is relational work
Prepare records for shipment by certified mail.
physical manipulation — Preparing physical mail requires hands-on assembly
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<script src="https://giniloh.com/embed.js" async></script> Community Sentiment
Do you agree with the AI automation risk score calculated for this occupation?
Method
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
See the full method →Related Article
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