Models
Models — AI exposure, safer roles, and a pivot plan.
Also known as: Art Model · Fit Model · Agent Model · Floor Model · Figure Model · Clothes Model
This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.
Most exposed tasks
Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.
No strongly automatable task in the current data release.
Augmentable tasks
Work where AI assists rather than replaces — the productivity frontier of this role.
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Report job completions to agencies and obtain information about future appointments.59
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Record rates of pay and durations of jobs on vouchers.57
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Work closely with photographers, fashion coordinators, directors, producers, stylists, make-up artists, other models, and clients to produce the desired looks, and to finish photo shoots on schedule.49
Most durable tasks
Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.
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Assemble and maintain portfolios, print composite cards, and travel to go-sees to obtain jobs.30
Task exposure values and classifications come from the versioned data release — they are structured data, not model output. Bars show exposure contribution relative to this role’s task mix.
What this means
A score of 42 puts Models in the second quartile of analyzed occupations. In practice, exposure this level is about the mix: 0 of 10 analyzed tasks lean automatable, 9 augmentable, and 1 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.
One next move: adopt AI deliberately on the augmentable tasks and build visible evidence of the durable ones.
Lower-exposure adjacent roles
Shown only when the target is at least 10 points lower under the same score version and skill overlap is at least 50%. These are adjacent roles with lower task exposure — not guaranteed “safe careers”.
Makeup Artists, Theatrical and Performance
28 ▼ 14 pts lower
Skill overlap ≈ 72% · Related O*NET role; Makeup Artists, Theatrical and Performance is an adjacent path (Moderate band).
Craft Artists
29 ▼ 13 pts lower
Skill overlap ≈ 56% · Related O*NET role; Craft Artists is an adjacent path (Moderate band).
Labor-market context
- $48,470median wage
- 3,780employed
- 1,200annual openings
- +0.0%projected growth
Context only — labor statistics are not inputs to the exposure score. See methodology.
Your week probably doesn’t match the average
This page scores the occupation. The $9 Personalized Risk & Action Report scores your task mix — paste what you actually do and get your own score, confidence level, task matrix, human moat, and a 7/30/90-day plan.
Personalize my result — $9Related roles
Adjacent by skills or family — no exposure claim implied.
FAQ — Models
- What does a score of 42 mean for a Models?
- It means that, weighted across the 10 tasks we analyzed for this role, the task mix sits at 42 on a 0–100 exposure scale — in the second quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
- Which tasks in this role are most exposed to AI?
- This role has no strongly automatable task in the current data release.
- Which parts of this job are most durable?
- The most durable responsibilities are: Assemble and maintain portfolios, print composite cards, and travel to go-sees to obtain jobs. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
- Is this score personalized to me?
- No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.
Score version jr-v1 · data release 2026.07.11-r1 · updated 2026-07-11 · baseline mapping: 10 of 10 tasks carry source-level provenance · methodology