Headline risk
3%
Very Low RiskAgents and business managers of artists, performers, and athletes
United States AI Work Index tracks this occupation on the shared structural baseline and then layers on local demand resilience, wages, and confidence.
Why This Score
Share of job tasks that overlap with current AI capabilities
Median annual wage
Projected employment change over 10 years
Typical preparation needed for this occupation
Occupation profile
Represent and promote artists, performers, and athletes in dealings with current or prospective employers. May handle contract negotiation and other business matters for clients.
Task evidence
100% weighted task match · 18% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 96,310
Employment 2024
21.4K
Projected Change (2024–34)
8.7%
Openings (2024–34)
2.2K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Send samples of clients' work and other promotional material to potential employers to obtain auditions, sponsorships, or endorsement deals. AI use: 0%
- 2. Keep informed of industry trends and deals. AI use: 95%
- 3. Collect fees, commissions, or other payments, according to contract terms. AI use: 0%
- 4. Conduct auditions or interviews to evaluate potential clients. AI use: 0%
- 5. Negotiate with managers, promoters, union officials, and other persons regarding clients' contractual rights and obligations. AI use: 0%
- 6. Confer with clients to develop strategies for their careers, and to explain actions taken on their behalf. AI use: 71%
Technologies
Requirements
Work context
Worker profile
Median age 43.3 · 60K employed
Under 25: 2% · 25–54: 73% · 55+: 23%
Related
Source coverage
11/11 source families · O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Mapping quality
title_match · employment series present
Narrative & sources
Published limitations
This page shows the local country layer, not realised individual job outcomes. The global structural baseline is shared across countries; only the local demand and wage layer changes here.
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.