AI exposure: Talent Directors
Audition and interview performers to select most appropriate talent for parts in stage, television, radio, or motion picture productions.
Reading this score
computed29.1% of this occupation's weighted task load is exposed, which puts Talent Directors at the 51th percentile of 923 occupations. The capability is largely there. Its average task scores 2.0 out of 4 on what a current system can produce, and the frictions that hold other jobs in place are comparatively weak here.
What holds the line here is context. Across this occupation's 15 tasks it averages 2.08 out of 3, the highest of the five friction dimensions. In plain terms, the work depends on knowledge the model cannot hold. Much of this job runs on things that were never written down: what this particular organisation does, what happened last week, what the person across the table actually meant. That context is the barrier, and it erodes as systems are given more access.
The most exposed thing this job does is Attend or view productions to maintain knowledge of available actors, at 86.7%. The least is Review performer information, at 10.0%. A gap of 76.7% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within arts, design, entertainment, sports and media occupations, this one is less exposed than the median of 38.5% across the group's 40 roles, with 29 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.
What would move this score. Of 15 tasks, 4 are currently banded exposed, 6 assisted and 5 untouched. For that distribution to shift materially would take systems being given deeper access to the organisation's own records and history, which is already happening. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Task by task
15 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Attend or view productions to maintain knowledge of available actors. | 86.7% | 13.3% | 0.0% | 3.43 | exposed |
| Maintain talent files that include information such as performers' specialties, past performances, and availability. | 80.0% | 20.0% | 0.0% | 3.97 | exposed |
| Read scripts and confer with producers to determine the types and numbers of performers required for a given production. | 50.0% | 25.0% | 25.0% | 3.65 | exposed |
| Negotiate contract agreements with performers, with agents, or between performers and agents or production companies. | 30.0% | 20.0% | 50.0% | 4.07 | exposed |
| Contact agents and actors to provide notification of audition and performance opportunities and to set up audition times. | 23.3% | 26.7% | 50.0% | 4.15 | assisted |
| Serve as liaisons between directors, actors, and agents. | 23.3% | 26.7% | 50.0% | 4.07 | assisted |
| Arrange for or design screen tests or auditions for prospective performers. | 23.3% | 26.7% | 50.0% | 4.05 | assisted |
| Locate performers or extras for crowd and background scenes, and stand-ins or photo doubles for actors, by direct contact or through agents. | 23.3% | 26.7% | 50.0% | 3.07 | assisted |
| Select performers for roles or submit lists of suitable performers to producers or directors for final selection. | 16.7% | 33.3% | 50.0% | 4.33 | assisted |
| Hire and supervise workers who help locate people with specified attributes and talents. | 16.7% | 33.3% | 50.0% | 3.50 | assisted |
| Prepare actors for auditions by providing scripts and information about roles and casting requirements. | 12.6% | 20.7% | 66.7% | 4.38 | untouched |
| Teach acting classes. | 11.7% | 13.3% | 75.0% | 3.19 | untouched |
| Direct shows, productions, and plays. | 10.8% | 14.2% | 75.0% | 3.53 | untouched |
| Audition and interview performers to match their attributes to specific roles or to increase the pool of available acting talent. | 10.0% | 15.0% | 75.0% | 4.39 | untouched |
| Review performer information, such as photos, resumes, voice tapes, videos, and union membership, to decide whom to audition for parts. | 10.0% | 15.0% | 75.0% | 4.03 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 2.02 | 0-4 |
| Embodiment | 1.06 | 0-3 |
| Presence | 2.03 | 0-3 |
| Accountability | 0.91 | 0-3 |
| Context | 2.08 | 0-3 |
| Verification cost | 1.38 | 0-3 |
What this means in practice
Where most of a role's weighted task load is exposed, the work that survives is usually the part of the job nobody wrote into the job description: deciding what should be produced rather than producing it, and being answerable for the result. The tasks lowest on this page are a better guide to where to spend your time than any general advice about the future of work.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.