Human-AI collaboration
Human-AI collaboration in accommodation and food services
Weighted by the 14.2 million jobs BLS counts in accommodation and food services, AI use with a classified collaboration pattern (excluding unclassified conversations) on this industry's occupations is 42.8% augmentation and 57.2% automation (Anthropic Economic Index, May 2026).
Data compiled 2026-10-09 · BLS 2025–35 · O*NET 31.0 · AEI May 2026
Augmentation share, employment-weighted
42.8%
Global Claude.ai conversations with a classified collaboration pattern (excluding unclassified conversations): 51.4% augmentation.
Anthropic Economic Index (May 2026)
At a glance
AI use and exposure across the industry's occupations
- 42.8%
Augmentation share of AI use
Shares exclude conversations with no classified collaboration pattern. Automation share: 57.2%. Occupations with usage data cover 94.9% of the industry's jobs.
Anthropic Economic Index (May 2026)
- 16%
Average LLM exposure (β)
Employment-weighted across occupations covering 99.3% of jobs. U.S. average: 30%.
Eloundou et al., Science 2024
- 2.1%
Jobs in high-exposure occupations
Share of covered 2025 jobs in occupations with β of 0.5 or more.
Eloundou et al., Science 2024 · BLS National Employment Matrix 2025–35
- 14.2 million
Jobs in 2025
BLS projects +4.3% to 14.8 million by 2035 (Accommodation and food services, NAICS 720000).
BLS National Employment Matrix 2025–35
Collaboration patterns
Employment-weighted mix of how people work with AI on this industry's tasks
The person hands over the whole task with minimal back-and-forth.
AI completes the task, guided by feedback such as error messages relayed by the person.
The person and AI refine the work together over several turns.
The person uses AI to understand a topic or build a skill.
The person asks AI to check or improve work they did.
Conversations that fit none of the patterns above.
Anthropic Economic Index (May 2026) · BLS National Employment Matrix 2025–35
Largest occupations
By 2025 employment in the industry
| Occupation | Jobs in industry, 2025 | Change to 2035 | Exposure (β) | Automation share |
|---|---|---|---|---|
| Fast Food and Counter Workers | 3.4 million | +6.4% | 7% | 52.5% |
| Waiters and Waitresses | 2.1 million | +1.7% | 22% | 59.9% |
| Cooks, Restaurant | 1.3 million | +12.2% | 12% | 71.5% |
| First-Line Supervisors of Food Preparation and Serving Workers | 1.0 million | +6.2% | 26% | 41.6% |
| Cooks, Fast Food | 620,200 | +0.5% | 3% | 73.8% |
| Bartenders | 601,600 | +4.6% | 14% | 46.8% |
| Food Preparation Workers | 517,500 | −2.6% | 5% | 79.0% |
| Dining Room and Cafeteria Attendants and Bartender Helpers | 451,100 | +5.8% | 0% | 75.0% |
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.
- 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.
- Industry figures weight each occupation's AEI shares by its 2025 employment in the industry from the BLS National Employment Matrix. Coverage shows the share of the industry's detailed-occupation employment with AEI data.
- Average exposure is the employment-weighted Eloundou et al. β; "high-exposure jobs" are occupations with β of 0.5 or more.
- 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.
BLS National Employment Matrix 2025–35
U.S. Bureau of Labor Statistics, Employment Projections program. 2025–35 National Employment Matrix, industry-occupation employment.
Vintage: 2025 base year, 2035 projection, released August 27, 2026. License: Public domain (U.S. federal government work). Retrieved 2026-10-09.
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.