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AI career impact

AI-augmented roles

How AI is used on the tasks of 79 occupations — augmenting people or automating work — from the Anthropic Economic Index (May 2026), with O*NET tasks and skills.

Data compiled 2026-10-09 · BLS 2025–35 · O*NET 31.0 · AEI May 2026

Global Claude.ai conversations with a classified collaboration pattern (excluding unclassified conversations), May 2026

51.4%

augmented the person rather than automating the task.

Anthropic Economic Index (May 2026)

At a glance

Occupations on this page, Anthropic Economic Index (May 2026)

43 of 79

Occupations where augmentation leads

Conversations on their tasks augment the person at least as often as they automate the work.

Anthropic Economic Index (May 2026)

All occupations

Sorted by augmentation share

Shares of global Claude.ai conversations mapped to each occupation's tasks: Anthropic Economic Index (May 2026). Augmentation and automation exclude unclassified collaboration patterns; work use includes them. Low-volume rows have under 0.05% of conversations.
OccupationAugmentationAutomationWork use
Medical Assistants72.5%27.5%8.6%
MachinistsLow volume — treat estimates with caution71.8%28.2%48.2%
Writers and Authors71.5%28.5%54.5%
News Analysts, Reporters, and Journalists71.2%28.8%49.3%
Graphic Designers70.4%29.6%75.0%
Lawyers68.5%31.5%52.2%
Dental HygienistsLow volume — treat estimates with caution67.6%32.4%3.9%
Elementary School TeachersLow volume — treat estimates with caution67.5%32.5%22.2%
Civil EngineersLow volume — treat estimates with caution66.9%33.1%73.1%
Cashiers66.6%33.4%20.7%
Customer Service Representatives65.7%34.3%11.1%
Pharmacists63.1%37.0%10.2%
Physical TherapistsLow volume — treat estimates with caution62.6%37.4%22.6%
Paralegals and Legal Assistants62.5%37.5%75.4%
Nurse Practitioners62.1%37.9%5.6%
Nursing Assistants62.0%38.0%7.4%
Marketing Managers61.6%38.4%74.5%
Public Relations Specialists61.2%38.9%77.6%
Technical Writers61.1%38.9%55.5%
Child, Family, and School Social WorkersLow volume — treat estimates with caution60.0%40.1%7.9%
Compliance Officers59.8%40.2%34.6%
Human Resources ManagersLow volume — treat estimates with caution59.5%40.5%78.1%
Industrial EngineersLow volume — treat estimates with caution59.0%41.0%61.4%
Retail Salespersons58.7%41.3%8.3%
Personal Financial Advisors58.4%41.6%25.1%
Pharmacy Technicians58.4%41.6%5.8%
Registered NursesLow volume — treat estimates with caution58.2%41.8%8.5%
Secondary School TeachersLow volume — treat estimates with caution58.1%41.9%37.9%
Human Resources SpecialistsLow volume — treat estimates with caution58.0%42.1%78.6%
Tax Preparers56.2%43.8%36.6%
Financial and Investment Analysts55.8%44.2%47.3%
General and Operations Managers55.6%44.4%80.9%
Accountants and Auditors55.0%45.0%67.6%
Management Analysts54.5%45.5%78.5%
Market Research Analysts and Marketing Specialists54.4%45.6%62.7%
Sales Representatives of Services54.3%45.7%47.1%
Loan Interviewers and ClerksLow volume — treat estimates with caution53.7%46.3%42.3%
Sales Representatives, Wholesale and Manufacturing53.1%46.9%11.8%
Real Estate Sales AgentsLow volume — treat estimates with caution52.9%47.1%26.3%
Data Scientists52.6%47.4%56.0%
Sales Managers52.2%47.8%54.6%
Training and Development Specialists52.1%47.9%76.0%
Financial Managers50.3%49.7%58.0%
TellersLow volume — treat estimates with caution49.2%50.8%46.9%
Physician AssistantsLow volume — treat estimates with caution49.0%51.0%16.6%
Web and Digital Interface Designers48.7%51.3%67.2%
Project Management Specialists48.5%51.5%61.1%
Bookkeeping, Accounting, and Auditing Clerks48.1%51.9%34.8%
Operations Research Analysts46.9%53.1%58.1%
Logisticians45.5%54.6%67.6%
Web Developers44.7%55.3%71.1%
Mechanical Engineers44.5%55.5%34.6%
Executive Secretaries and Executive Administrative Assistants43.0%57.0%61.5%
Receptionists and Information Clerks41.4%58.6%43.2%
Electrical EngineersLow volume — treat estimates with caution41.0%59.0%46.5%
Waiters and Waitresses40.1%59.9%2.8%
Software Developers39.2%60.8%77.2%
Loan Officers39.2%60.8%36.8%
ElectriciansLow volume — treat estimates with caution39.2%60.8%70.9%
Database Administrators37.2%62.8%54.6%
Interpreters and Translators36.9%63.1%38.5%
Medical and Health Services Managers36.9%63.1%90.4%
Computer and Information Systems Managers34.9%65.1%52.5%
Heavy and Tractor-Trailer Truck DriversLow volume — treat estimates with caution34.9%65.2%55.9%
Computer User Support Specialists34.4%65.6%45.7%
Network and Computer Systems Administrators31.9%68.1%59.5%
General Office Clerks30.7%69.3%60.3%
Plumbers, Pipefitters, and SteamfittersLow volume — treat estimates with caution29.8%70.2%34.0%
Secretaries and Administrative Assistants29.4%70.6%70.4%
Restaurant CooksLow volume — treat estimates with caution28.5%71.5%14.1%
HVAC Mechanics and InstallersLow volume — treat estimates with caution27.4%72.6%42.2%
Automotive Service Technicians and MechanicsLow volume — treat estimates with caution26.4%73.6%41.3%
Medical Records SpecialistsLow volume — treat estimates with caution25.1%74.9%59.8%
General Maintenance and Repair WorkersLow volume — treat estimates with caution24.3%75.7%9.9%
Software Quality Assurance Analysts and Testers24.2%75.8%72.8%
Information Security AnalystsLow volume — treat estimates with caution23.9%76.1%80.0%
CarpentersLow volume — treat estimates with caution22.2%77.8%83.8%
Computer Systems Analysts15.8%84.2%56.7%
Security GuardsLow volume — treat estimates with caution13.3%86.7%27.0%

Sources & methodology

Every figure on this page comes from the public datasets below. We do not edit the source values; derived figures are explained here.

  1. Collaboration shares come from Anthropic Economic Index data for Claude.ai conversations in May 2026, classified to the O*NET tasks they match. "Automation" groups directive and feedback-loop conversations; "augmentation" groups task iteration, learning, and validation. Both buckets are shares of conversations with a classified collaboration pattern, excluding the unclassified "none" pattern; the six individual pattern shares include unclassified conversations. They describe how people use Claude on this occupation's tasks — not what share of workers in the occupation use AI.
  2. Conversation share is this occupation's percentage of all classified Claude.ai conversations. Rows under 0.05% are flagged as low-volume; read their percentages with caution.
  3. Core tasks are the O*NET 31.0 core task statements ranked by O*NET importance; skills are the O*NET importance ratings (1–5).
  4. BLS occupations are matched to O*NET-SOC codes with the BLS O*NET-to-NEM crosswalk; where a BLS occupation spans several O*NET occupations, we average their values.
  • Anthropic Economic Index (May 2026)

    Massenkoff, M., Lyubich, E., Sacher, S., Hitzig, Z., Zhang, S., Heller, R., & McCrory, P. (2026). "Anthropic Economic Index report: Cadences." Anthropic, June 26, 2026. Claude.ai usage metrics by occupation, global, May 2026.

    Vintage: Release of June 26, 2026; Claude.ai conversations from May 2026. License: CC BY (data). Retrieved 2026-10-09.

  • O*NET 31.0 Database

    This page includes information from the O*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. Metaintro has modified all or some of this information. USDOL/ETA has not approved, endorsed, or tested these modifications.

    Vintage: O*NET 31.0, August 2026 release. License: CC BY 4.0. Retrieved 2026-10-09.

  • Eloundou et al., Science 2024

    Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2024). "GPTs are GPTs: Labor market impact potential of LLMs." Science, 384(6702), 1306–1308. doi:10.1126/science.adj0998. Occupation- and task-level exposure data from the authors' public repository (openai/GPTs-are-GPTs).

    Vintage: Published June 21, 2024; human annotations of O*NET tasks collected 2023. License: Data repository: MIT License. Retrieved 2026-10-09.

  • BLS Employment Projections 2025–35

    U.S. Bureau of Labor Statistics, Employment Projections program. Occupational projections, 2025–35, and worker characteristics, 2025 (Table 1.2); fastest growing occupations (Table 1.3); factors affecting occupational utilization (Table 1.12).

    Vintage: 2025–35 projections, released August 27, 2026. License: Public domain (U.S. federal government work). Retrieved 2026-10-09.

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