AI Automation Index

Will AI Replace Agents and Business Managers of Artists, Performers, and Athletes?

Task-level automation exposure for Agents and Business Managers of Artists, Performers, and Athletes: 14 O*NET tasks scored against their work activities, plus the simulator.

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Automation Exposure

45% weighted task index

14 of 14 tasks scored

Median Salary

$82,890 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Low

12,620 people hold this job — size, not growth

Projected 2025–35

+9.7% employment change

2,400 openings a year · BLS line item

Pay by state

BLS OEWS publishes 17 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$56,560 – $98,200

Highest medians

Florida $98,200

California $98,110

Colorado $95,530

Texas $82,920

Michigan $82,440

Lowest medians

Illinois $56,560

Arizona $60,340

Virginia $73,400

Washington $74,620

Wisconsin $74,990

State figures come from the 13-1011 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

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.

Automation potential 45%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 0%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 18%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 5%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 10/100 Low

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.

Constituent Task Mix

14 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 22%

3 tasks

Medium exposure (≥ 35%) 56%

8 tasks

Low exposure (below 35%) 21%

3 tasks

How would you survive?

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 →

Constituent Tasks

#12865 · Core · 35% automatable

Collect fees, commissions, or other payments, according to contract terms.

physical manipulation — In-person payment handling; some digital automation

Collect payments for goods or services.

#21163 · Core · 39% automatable

Send samples of clients' work and other promotional material to potential employers to obtain auditions, sponsorships, or endorsement deals.

text generation — Campaign content and analysis drafted; human executes strategy

Perform marketing activities. Distribute promotional literature or samples to customers.

#12870 · Core · 78% automatable

Keep informed of industry trends and deals.

information retrieval — AI surfaces updates; human internalizes knowledge

Update professional knowledge.

#12872 · Core · 42% automatable

Conduct auditions or interviews to evaluate potential clients.

interpersonal — Live interview judgment and rapport; AI can only screen

Conduct eligibility or selection interviews.

#12869 · Core · 20% automatable

Negotiate with managers, promoters, union officials, and other persons regarding clients' contractual rights and obligations.

interpersonal — Collective bargaining is high-stakes live negotiation

Arrange collective bargaining agreements.

#12866 · Core · 72% automatable

Confer with clients to develop strategies for their careers, and to explain actions taken on their behalf.

text generation — Written correspondence to customers is largely automatable

Correspond with customers to answer questions or resolve complaints.

#12867 · Core · 25% automatable

Develop contacts with individuals and organizations, and apply effective strategies and techniques to ensure their clients' success.

interpersonal — Business relationships require human trust and presence

Develop business relationships.

#12868 · Core · 40% automatable

Schedule promotional or performance engagements for clients.

decision support — Planning aided; on-site execution is human

Organize special events.

#12873 · Core · 40% automatable

Arrange meetings concerning issues involving their clients.

decision support — Planning aided; on-site execution is human

Organize special events.

#12871 · Supplemental · 45% automatable

Manage business and financial affairs for clients, such as arranging travel and lodging, selling tickets, and directing marketing and advertising activities.

text generation — Marketing content and plans drafted; human executes

Implement financial decisions. Market products, services, or events.

#12877 · Supplemental · 55% automatable

Hire trainers or coaches to advise clients on performance matters, such as training techniques or performance presentations.

decision support — AI coordinates admin; human owns hiring decisions

Administer personnel recruitment or hiring activities.

#12874 · Supplemental · 82% automatable

Prepare periodic accounting statements for clients.

text generation — Standard financial documents drafted from data

Prepare financial documents.

#12876 · Supplemental · 22% automatable

Obtain information about or inspect performance facilities, equipment, and accommodations to ensure that they meet specifications.

visual inspection — Physical spec verification of facilities/equipment

Inspect facilities or equipment to ensure specifications are met.

#12875 · Supplemental · 53% automatable

Advise clients on financial and legal matters, such as investments and taxes.

decision support — Compliance guidance drafted; human verifies and owns

Advise others on legal or regulatory compliance matters. Recommend investments to clients.

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Community Sentiment

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Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

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 →

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