Will AI replace Set and Exhibit Designers?

Not as a job, but it is already doing parts of the work. Across the 27 official task statements scored for Set and Exhibit Designers (United States, SOC 27-1027), 15% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 33 out of 100 (range 27–39, band: low). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

Which tasks in “Set and Exhibit Designers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Provide supportive materials for exhibits and displays, such as press kits, advertising, publicity notices, posters, brochures, catalogues, and invitations” (83/100, very high); “Estimate set- or exhibit-related costs, including materials, construction, and rental of props or locations” (75/100, high); “Read scripts to determine location, set, and design requirements” (75/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “Set and Exhibit Designers” stay human?

About 68% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Attend rehearsals and production meetings to obtain and share information related to sets” (6/100, minimal); “Direct and coordinate construction, erection, or decoration activities to ensure that sets or exhibits meet design, budget, and schedule requirements” (6/100, minimal); “Observe sets during rehearsals in order to ensure that set elements do not interfere with performance aspects such as cast movement and camera angles” (7/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.

What should someone working in “Set and Exhibit Designers” do about AI?

Start from the ledger rather than the headline: 15% of this job's weighted core work is exposed, and roughly 68% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.

How is the AI exposure score for Set and Exhibit Designers calculated?

Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 27 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

US dataswitch to UK

Set and Exhibit Designers

developing set designs, collaborating with those in charge of lighting and sound so that those production aspects can be coordinated with set designs or exhibit layouts and designing and building scale models of set designs. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: attending rehearsals and production meetings to obtain and share information related to sets is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 15%
changing shape: 18%
staying human: 68%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 33 out of 100 (27–39 allowing for uncertainty): low exposure, across 27 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for set and exhibit designers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

What shifts is reading scripts to determine location: the paper around the work, not the work.

Your week, as this page understands it

Design special exhibits and sets for film, video, television, and theater productions. May study scripts, confer with directors, and conduct research to determine appropriate architectural styles. The job title says “set” or “exhibit designers”: officially one job, two names. The real job is the part underneath: attending rehearsals and production meetings to obtain and share information related to sets. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But set and exhibit designers is not one task. It is 27 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is attending rehearsals and production meetings to obtain and share information related to sets, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 15%
changing shape: 18%
staying human: 68%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

4 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

4 tasks

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Reading scripts to determine location
This is reading one thing and writing another: scripts in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Read scripts to determine location, set, and design requirements.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reading a script to pull out location, set and design requirements is document work software handles quickly and thoroughly.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Researching architectural and stylistic elements appropriate to the time period
This is reading one thing and writing another: architectural in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Research architectural and stylistic elements appropriate to the time period to be depicted, consulting experts for information, as necessary.” (O*NET task statement)
How this row was scored
Exposure score: 70 out of 100 (66–74 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Researching the architecture and style of a period draws on abundant published material.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Estimating set- or exhibit-related costs
This is reading one thing and writing another: set- in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Estimate set- or exhibit-related costs, including materials, construction, and rental of props or locations.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Costing materials, construction and rentals is arithmetic against price lists that software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Providing supportive materials for exhibits and displays
This is reading one thing and writing another: supportive materials in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Provide supportive materials for exhibits and displays, such as press kits, advertising, publicity notices, posters, brochures, catalogues, and invitations.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Press kits, posters, brochures and invitations are standard promotional writing software drafts well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.

Changing shape

4 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Preparing rough drafts and scale working drawings of sets
The software now makes the first pass at rough drafts, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Prepare rough drafts and scale working drawings of sets, including floor plans, scenery, and properties to be constructed.” (O*NET task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Concept layouts come easily, but accurate scale construction drawings depend on the specific venue and build.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Preparing preliminary renderings of proposed exhibits
The software now makes the first pass at preliminary renderings of proposed exhibits, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Prepare preliminary renderings of proposed exhibits, including detailed construction, layout, and material specifications, and diagrams relating to aspects such as special effects or lighting.” (O*NET task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Renderings are quick to generate, but the construction and material detail depends on the actual space.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Submitting plans for approval
The software now makes the first pass at plans, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Submit plans for approval, and adapt plans to serve intended purposes, or to conform to budget or fabrication restrictions.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Reworking plans to fit a budget needs the real costs and constraints of that production.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.

Staying human

19 tasks

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Developing set designs, based on evaluation of scripts, budgets, research information and available locations
The ratings behind this row put set designs well outside what today's tools can do on their own.
importance 5 · Core
Source: “Develop set designs, based on evaluation of scripts, budgets, research information, and available locations.” (O*NET task statement)
How this row was scored
Exposure score: 37 out of 100 (30–44 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Software can propose set concepts from a script, but the design that actually works comes from the designer.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Attending rehearsals and production meetings to obtain and share information related to sets
This work happens in the physical world: rehearsals, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Attend rehearsals and production meetings to obtain and share information related to sets.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Rehearsals and production meetings are about being in the room as things change.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Conferring with clients and staff to gather information about exhibit space
The value here is that a specific person handles clients and stands behind it. That is earned, not computed.
importance 5 · Core
Source: “Confer with clients and staff to gather information about exhibit space, proposed themes and content, timelines, budgets, materials, or promotion requirements.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: What a client actually needs from an exhibit comes out through conversation with them and their staff.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.

Show the other 17 tasks

Selecting and purchasing lumber and hardware necessary for set construction
changing shape
The software now makes the first pass at lumber, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Select and purchase lumber and hardware necessary for set construction.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working out and ordering the lumber and hardware needed is a documented, catalog-based task.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Planning for location-specific issues, such as space limitations, traffic flow patterns and safety concerns
staying human
The ratings behind this row put location-specific issues well outside what today's tools can do on their own.
importance 4 · Core
Source: “Plan for location-specific issues, such as space limitations, traffic flow patterns, and safety concerns.” (O*NET task statement)
How this row was scored
Exposure score: 33 out of 100 (26–40 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Space limits, crowd flow and safety follow documented rules, but the deciding details belong to that venue.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Incorporating security systems into exhibit layouts
staying human
The ratings behind this row put security systems well outside what today's tools can do on their own.
importance 3 · Supplemental
Source: “Incorporate security systems into exhibit layouts.” (O*NET task statement)
How this row was scored
Exposure score: 33 out of 100 (26–40 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Security requirements are documented, but fitting them to a particular exhibit and building takes local knowledge.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Acquiring or arranging
staying human
The ratings behind this row put this work well outside what today's tools can do on their own.
importance 3 · Core
Source: “Acquire, or arrange for acquisition of, specimens or graphics required to complete exhibits.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Finding and arranging for specimens or graphics is sourcing work built on conversations and availability.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Conferring with conservators to determine how to handle an exhibit's environmental aspects
staying human
The ratings behind this row put conservators well outside what today's tools can do on their own.
importance 4 · Supplemental
Source: “Confer with conservators to determine how to handle an exhibit's environmental aspects, such as lighting, temperature, and humidity, so that objects will be protected and exhibits will be enhanced.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Lighting, temperature and humidity limits are published conservation standards that software can apply to a given object.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Assigning staff to complete design ideas and prepare sketches
staying human
The ratings behind this row put staff well outside what today's tools can do on their own.
importance 4 · Core
Source: “Assign staff to complete design ideas and prepare sketches, illustrations, and detailed drawings of sets, or graphics and animation.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Allocating design work can be planned by software, but knowing which designer suits which job is personal.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Designing and producing displays and materials that can be used to decorate windows
staying human
This work happens in the physical world: displays, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Design and produce displays and materials that can be used to decorate windows, interior displays, or event locations, such as streets and fairgrounds.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Designing a display suits software well; producing and installing it is physical work.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Arranging for outside contractors to construct exhibit structures
staying human
The value here is that a specific person handles outside contractors and stands behind it. That is earned, not computed.
importance 3 · Supplemental
Source: “Arrange for outside contractors to construct exhibit structures.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Arranging contractors depends on relationships, availability and negotiation with specific firms.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Selecting set props, such as furniture, pictures, lamps and rugs
staying human
This work happens in the physical world: set props, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Select set props, such as furniture, pictures, lamps, and rugs.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Software can suggest period-appropriate props, but choosing and sourcing the actual pieces means seeing them.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Coordinating the transportation of sets that are built off-site
staying human
This work happens in the physical world: the transportation of sets, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Coordinate the transportation of sets that are built off-site, and coordinate their setup at the site of use.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Transport planning is documented logistics, but the setup happens at the venue with people and trucks.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Collaborating with those in charge of lighting and sound so that those production aspects can be coordinated with set designs or exhibit layouts
staying human
The value here is that a specific person handles this work and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Collaborate with those in charge of lighting and sound so that those production aspects can be coordinated with set designs or exhibit layouts.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Coordinating with lighting and sound depends on people working out a shared solution together.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Examining objects to be included in exhibits to plan where and how to display them
staying human
This work happens in the physical world: objects, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine objects to be included in exhibits to plan where and how to display them.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Deciding how to display an object usually means having the object in front of you.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Designing and building scale models of set designs
staying human
This work happens in the physical world: scale models of set designs, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Design and build scale models of set designs, or miniature sets used in filming backgrounds or special effects.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Designing the model is screen work; building a physical scale model is handwork.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Inspecting installed exhibits for conformance to specifications and satisfactory operation of special-effects components
staying human
This work happens in the physical world: installed exhibits, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect installed exhibits for conformance to specifications and satisfactory operation of special-effects components.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking an installed exhibit works properly means walking around it and trying it.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Coordinating the removal of sets
staying human
This work happens in the physical world: the removal of sets, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Coordinate the removal of sets, props, and exhibits after productions or events are complete.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Striking sets and clearing exhibits is physical work done at the venue afterwards.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Observing sets during rehearsals
staying human
This work happens in the physical world: sets during rehearsals, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Observe sets during rehearsals in order to ensure that set elements do not interfere with performance aspects such as cast movement and camera angles.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Spotting that a set piece blocks an actor or a camera means watching the rehearsal in the space.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Directing and coordinating construction, erection or decoration activities to ensure that sets or exhibits meet design, budget and schedule requirements
staying human
This work happens in the physical world: construction, erection or decoration activities, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Direct and coordinate construction, erection, or decoration activities to ensure that sets or exhibits meet design, budget, and schedule requirements.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Directing a build or install crew means being on site as the work happens.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: $75,240a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 10,630in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: rough drafts in, a record out. The rows above are exactly that shape: reading scripts to determine location and researching architectural and stylistic elements appropriate to the time period. What it cannot do is be there in the room, and that is still where rehearsals get done. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

Start with what does not change: attending rehearsals and production meetings to obtain and share information related to sets is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 15% of this job's task weight sits in rows the software is already learning, 18% in rows that change shape rather than disappear, and 68% in rows it is nowhere near. That is the position, measured across 27 scored tasks. It is not a forecast about you.

So the thing worth your attention is not the job going away. It is the layer around it. Reading scripts to determine location is the part turning into software, and being the person who understands that layer is worth money.

This week: one thing

Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to rough drafts, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.

What you end up holding: a straight answer about what is actually being rolled out, and when
How long it takes: ten minutes

If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether set designs are in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near preparing rough drafts and scale working drawings of sets. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.

Over the next 12 months

On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to set and exhibit designers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was merchandise displayers and window trimmers: only about 4% of its durable work is work you already do and it pays 47.6% less. And on the numbers you do not need one. This job scores 33/100 here, with only 15% of the task list in the top band, and “develop set designs, based on evaluation of scripts, budgets, research information, and…” is not work that hands over cleanly. None of them beats deepening what you already have.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Merchandise Displayers and Window Trimmers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine objects to be included in exhibits to plan where and how to…, and their equivalent is to install booths, exhibits, displays, carpets, or drapes, as guided by floor plan of…. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $39,390 against your $75,240, 47.6% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Fine Artists, Including Painters, Sculptors, and Illustrators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine objects to be included in exhibits to plan where and how to…, and their equivalent is to set up exhibitions of artwork for display or sale. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $55,490 against your $75,240, 26.2% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Camera Operators, Television, Video, and Film
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already read scripts to determine location, set, and design requirements, and their equivalent is to observe sets or locations for potential problems and to determine filming and lighting…. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 15% of its task weight, across 27 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like attending rehearsals and production meetings to obtain and share information related to sets arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

If you run a team doing this job

If you run a team doing this job, the conversation you owe them is the one on this page, and sooner than feels comfortable. Show them the ledger rather than a reassurance: the rows moving toward the software are reading scripts to determine location, and the rows that are not are where you want your people visible. Ask each of them to do the this-week move and bring the list to your next one-to-one. It turns a rumour into a piece of work, and it tells you which parts of your team's week are actually at stake. And say the thing out loud that a team lead usually leaves unsaid: a shrinking team is your exposure too, so do the move yourself as well.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Visual merchandisers and related occupations is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

The other groups this work is counted across:

Interior designers

In UK official statistics this job is counted as Visual merchandisers and related occupations and Interior designers. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for set / exhibit designers, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 15% of the work on this page is already inside what they can do.

Try The AI Authority free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

The AI Authority is a general community about working with AI, not a course for set / exhibit designers. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

Noted, and thank you. We’ll email you if a Space for set / exhibit designers launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.

No Space for set / exhibit designers yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for set / exhibit designers existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for set / exhibit designers launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Set and Exhibit Designers?: Not as a job, but it is already doing parts of the work. Across the 27 official task statements scored for Set and Exhibit Designers (United States, SOC 27-1027), 15% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 33 out of 100 (range 27–39, band: low). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Set and Exhibit Designers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Provide supportive materials for exhibits and displays, such as press kits, advertising, publicity notices, posters, brochures, catalogues, and invitations” (83/100, very high); “Estimate set- or exhibit-related costs, including materials, construction, and rental of props or locations” (75/100, high); “Read scripts to determine location, set, and design requirements” (75/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Set and Exhibit Designers” stay human?: About 68% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Attend rehearsals and production meetings to obtain and share information related to sets” (6/100, minimal); “Direct and coordinate construction, erection, or decoration activities to ensure that sets or exhibits meet design, budget, and schedule requirements” (6/100, minimal); “Observe sets during rehearsals in order to ensure that set elements do not interfere with performance aspects such as cast movement and camera angles” (7/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Set and Exhibit Designers” do about AI?: Start from the ledger rather than the headline: 15% of this job's weighted core work is exposed, and roughly 68% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Set and Exhibit Designers calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 27 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
4 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

How we score a job Download this release Look up another job

Using these figures?

Cite this

Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.