Talent Directors
In short: today's best AI models could do about 59% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 61% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 39% of the time, stays with people.
Audition and interview performers to select most appropriate talent for parts in stage, television, radio, or motion picture productions.
$90,360 a year (for the broader BLS group this job sits in).
A typical 40-hour week
Not yet reviewed task by task- AI could take on23 h
- A person checks AI's work0 h
- Desk work AI can't do yet1 h
- Stays with people16 h
Talent Directors, now: of a 40-hour week, AI could take on 23 hours, 0 hours become checking its work, 1 hours are desk work it can't do yet, and 16 hours stay with people.
The largest pieces: Arrange for or design screen tests or auditions for prospective performers (about 4 h); Maintain talent files that include information such as performers' specialties, past performances, and availability (about 3 h); Select performers for roles or submit lists of suitable performers to producers or directors for final selection (about 3 h).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 61%
- 15%
- 24%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 30%. Today's estimate: 59%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 15 tasks showed up. Within each of Anthropic's methods, never across a change: 0.015% to 0.034% (released February and March 2025); 0.0094% to 0.029% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.015% | 487 of 708 | 4 of 15 |
| Released March 2025 | 0.034% | 341 of 703 | 6 of 15 |
| The week of Aug 4, 2025 (released September 2025) | 0.0094% | 464 of 655 | 3 of 15 |
| The week of Nov 13, 2025 (released January 2026) | 0.03% | 319 of 672 | 7 of 15 |
| The week of Feb 5, 2026 (released March 2026) | 0.029% | 345 of 677 | 6 of 15 |
| April 2026 (released June 2026) | none | n/a | 0 of 15 |
| May 2026 (released June 2026) | none | n/a | 0 of 15 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates almost none of this job's working time as physical work, so robots do not reach it.
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 15 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Direct shows, productions, and plays.Done more than yearly by most who do it. | 21% | 2.1 work days6.7 h to 4.2 work days | Stays with people | |
| Arrange for or design screen tests or auditions for prospective performers.Done more than yearly by most who do it. | 12% | 3.3 h50 min to 6.7 h | 91%Half by now | |
| Read scripts and confer with producers to determine the types and numbers of performers required for a given production.Done more than yearly by most who do it. AI observed on this task. | 9% | 3.3 h50 min to 1 work day | 86%Half by now | |
| Maintain talent files that include information such as performers' specialties, past performances, and availability.Done daily by most who do it. | 8% | 1.7 h25 min to 3.3 h | 99%Half by now | |
| Audition and interview performers to match their attributes to specific roles or to increase the pool of available acting talent.Done more than monthly by most who do it. | 8% | 1.3 h38 min to 2.5 h | Stays with people | |
| Select performers for roles or submit lists of suitable performers to producers or directors for final selection.Done more than weekly by most who do it. | 8% | 1.7 h25 min to 4.2 h | 97%Half by now | |
| Serve as liaisons between directors, actors, and agents.Done more than weekly by most who do it. | 8% | 50 min25 min to 1.7 h | 100%Half by now | |
| Review performer information, such as photos, resumes, voice tapes, videos, and union membership, to decide whom to audition for parts.Done daily by most who do it. | 7% | 1.3 h25 min to 3.3 h | 99%Half by now | |
| Negotiate contract agreements with performers, with agents, or between performers and agents or production companies.Done more than monthly by most who do it. | 4% | 2.1 h50 min to 4.2 h | Stays with people | |
| Prepare actors for auditions by providing scripts and information about roles and casting requirements.Done more than yearly by most who do it. | 3% | 25 min13 min to 50 min | 100%Half by now | |
| Contact agents and actors to provide notification of audition and performance opportunities and to set up audition times.Done more than yearly by most who do it. | 3% | 38 min13 min to 1.7 h | 100%Half by now | |
| Teach acting classes.Done more than yearly by most who do it. | 3% | 2.5 h1.3 h to 5 h | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
- Motion Picture and Video Industries37,700 people
- Media Streaming Distribution Services, Social Networks, and Other Media Networks and Content Providers23,000 people
- Radio and Television Broadcasting Stations18,570 people
- Performing Arts Companies8,270 people
- Advertising, Public Relations, and Related Services8,240 people
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Talent Directors is within reach of AI now?
- An estimated 59% of the working time is within reach of AI models now and 61% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Talent Directors come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Arrange for or design screen tests or auditions for prospective performers (91% of the task's time now, 100% by the end of 2028); Maintain talent files that include information such as performers' specialties, past performances, and availability (99% of the task's time now); and Select performers for roles or submit lists of suitable performers to producers or directors for final selection (97% of the task's time now).
- Which tasks of Talent Directors stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Direct shows, productions, and plays; Audition and interview performers to match their attributes to specific roles or to increase the pool of available acting talent; and Negotiate contract agreements with performers, with agents, or between performers and agents or production companies. Together such tasks are about 39% of the working time.
- Do people already use AI for the work of Talent Directors?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 9%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Talent Directors?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 15 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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