Will AI replace Word Processors and Typists?
On paper, AI could touch ~74% of the work in Word Processors and Typists — and unlike most jobs, it's already showing up in the real workday, not just the theory.
O*NET-SOC 43-9022
How your 17 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a high share of this job's tasks (~74%). By late 2025, real-world AI use had reached about 24% of its task activity (already common). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
Read this as a range, not a verdict
The signals here partly disagree — AI's theoretical reach (~74%) and its real-world use (~24%) tell different stories. AI-risk scores also shift a lot by which model does the rating (2.7%–51.5% in one 2026 study), so this is a direction of travel, not a fixed answer.
See all 17 tasks, ratedBased on real task-level AI scores — click to collapse
- Check completed work for spelling, grammar, punctuation, and format.
- File and store completed documents on computer hard drive or disk, or maintain a computer filing system to store, retrieve, update, and delete documents.
- Address envelopes or prepare envelope labels, using typewriter or computer.
- Type correspondence, reports, text and other written material from rough drafts, corrected copies, voice recordings, dictation, or previous versions, using a computer, word processor, or typewriter.
- Gather, register, and arrange the material to be typed, following instructions.
- Compute and verify totals on report forms, requisitions, or bills, using adding machine or calculator.
- Keep records of work performed.
- Electronically sort and compile text and numerical data, retrieving, updating, and merging documents as required.
- Search for specific sets of stored, typed characters to make changes.
- Collate pages of reports and other documents.
- Reformat documents, moving paragraphs or columns.
- Adjust settings for format, page layout, line spacing, and other style requirements.
- Use data entry devices, such as optical scanners, to input data into computers for revision or editing.
- Perform other clerical duties, such as answering telephone, sorting and distributing mail, running errands or sending faxes.
- Print and make copies of work.
- Transmit work electronically to other locations.
- Operate and resupply printers and computers, changing print wheels or fluid cartridges, adding paper, and loading blank tapes, cards, or disks into equipment.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.