Share and intensity of work current AI systems can materially affect.
SOC 27-2011
Actors AI displacement risk
Digital doubles and synthetic performers now handle background and some commercial work, which drove recent strikes and contract fights. Embodied performance, live theatre, emotional range, and star identity remain irreducibly human.
Likely potential for exposed tasks to move to software after workflow integration.
The synthetic-media threat is concentrated in background, voiceover, and likeness licensing — the areas unions are actively regulating. Principal performance and live work remain protected by audience preference for humans.
Distribution
Where Actors sits across 620 tracked roles
Displacement pressure 38 — higher than 65% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-08. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
18 O*NET task statements matched to SOC 27-2011. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $48,530 (Fallback estimate; May 2025 median unavailable, US national). BLS does not publish an exact current median for this occupational split, so the page retains a clearly labeled fallback estimate.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Actors
SOC 27-2011 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 38/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Actors
The current evidence import matched 18 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks18
SOC27-2011
- Core task / ID 7648
Attend auditions and casting calls to audition for roles.
- Core task / ID 7644
Work closely with directors, other actors, and playwrights to find the interpretation most suited to the role.
- Core task / ID 7649
Portray and interpret roles, using speech, gestures, and body movements, to entertain, inform, or instruct radio, film, television, or live audiences.
- Core task / ID 7643
Study and rehearse roles from scripts to interpret, learn and memorize lines, stunts, and cues as directed.
- Core task / ID 7646
Collaborate with other actors as part of an ensemble.
- Core task / ID 7645
Learn about characters in scripts and their relationships to each other to develop role interpretations.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Portray characters on stage or screen
Exposure 22, automation 6%, augmentation 30%.
Rehearse scripts and memorize roles
Exposure 30, automation 10%, augmentation 40%.
O*NET evidence: Study and rehearse roles from scripts to interpret, learn and memorize lines, stunts, a... (ID 7643)
Record voiceover and narration
Exposure 64, automation 44%, augmentation 48%.
O*NET evidence: Write original or adapted material for dramas, comedies, puppet shows, narration, or ot... (ID 7654)
Audition and promote work
Exposure 36, automation 14%, augmentation 44%.
O*NET evidence: Attend auditions and casting calls to audition for roles. (ID 7648)
TaskExposureAutomationAugmentation
Portray characters on stage or screen226%30%
Rehearse scripts and memorize roles3010%40%
Record voiceover and narration6444%48%
Audition and promote work3614%44%
Transition pathways
Adjacent moves that preserve existing skills
adjacent role
ModerateActing Coach
Training horizon: 2-6 months. Skill overlap 74. Wage preservation signal 96.
- Build a coaching client base
- Develop scene-study curriculum
- Record coaching testimonials
role redesign
ModerateContent Creator
Training horizon: 3-6 months. Skill overlap 62. Wage preservation signal 110.
- Build an owned audience channel
- Produce short-form performance content
- Monetize through multiple streams
Comparison guides
Compare the next move before you commit
2-6 months
Actors to Acting Coach
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Actors into Acting Coach.
3-6 months
Actors to Content Creator
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Actors into Content Creator.
What the AI risk score means for Actors
The displacement pressure score for Actors is 38. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Record voiceover and narration carries 44% automation pressure, while Record voiceover and narration carries 48% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $48,530 (Fallback estimate; May 2025 median unavailable, US national). Employment context: Project-based performance occupation with strong union presence. Typical education: No formal credential required; conservatory training common.
Wage vulnerability is 68, while transition feasibility is 60. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Moderate synthetic-media pressure
- Union contracts are shaping AI use
- Live performance stays human
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Actors, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Emotional performance
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Physical embodiment
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Voice craft
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Self-promotion
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Acting Coach, such as build a coaching client base.
- By 90 days, compare internal openings and external postings for Acting Coach or Content Creator and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Actors
Will AI replace Actors?
Digital doubles and synthetic performers now handle background and some commercial work, which drove recent strikes and contract fights. Embodied performance, live theatre, emotional range, and star identity remain irreducibly human. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Actors work are most exposed to AI?
Record voiceover and narration and Audition and promote work show the strongest automation pressure in this model. Record voiceover and narration and Audition and promote work are better treated as AI-augmented work.
What should Actors learn next?
Start with Emotional performance, Physical embodiment, Voice craft. The most practical adjacent paths in this model are Acting Coach and Content Creator.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureOECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics