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AI Automation Index
Will AI Replace Interior Designers?
Task-level automation exposure for Interior Designers: 16 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
49%
weighted task index
16 of 16 tasks scored
Median Salary
$67,190 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Medium
71,500 people hold this job — size, not growth
Projected 2025–35
+2.7%
employment change
7,700 openings a year · BLS line item
Pay by state
BLS OEWS publishes 50 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$32,150 – $98,450
Highest medians
District of Columbia $98,450
Wyoming $96,100
California $80,230
Massachusetts $80,110
Colorado $78,390
Lowest medians
Puerto Rico $32,150
Mississippi $43,740
West Virginia $49,800
Iowa $58,040
Rhode Island $58,100
State figures come from the 27-1025 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 49%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 49%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 0%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 6%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 4/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
16 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 22%
4 tasks
Medium exposure (≥ 35%) 59%
9 tasks
Low exposure (below 35%) 19%
3 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- Revision 08/2024 · Occupational Expert
Review contractor bids to subcontract fabrication, installation, and arrangement of carpeting, fixtures, accessories, draperies, paint and wall coverings, art work, furniture, and related items.
Replaced: Subcontract fabrication, installation, and arrangement of carpeting, fixtures, accessories, draperies, paint and wall coverings, art work, furniture, and related items.
Constituent Tasks
#20996 · Core · 55% automatable
Design plans to be safe and to be compliant with the American Disabilities Act (ADA).
decision support — Layout planning aided; human owns design
Plan facility layouts or designs.
#18521 · Core · 45% automatable
Use computer-aided drafting (CAD) and related software to produce construction documents.
visual inspection — AI aids illustrations; precise technical drawing human
Draw detailed or technical illustrations.
#23995 · Core · 67% automatable
Research health and safety code requirements to inform design.
information retrieval — AI surfaces updates; human internalizes knowledge
Conduct research to inform art, designs, or other work. Update professional knowledge.
#1735 · Core · 48% automatable
Confer with client to determine factors affecting planning of interior environments, such as budget, architectural preferences, purpose, and function.
interpersonal — Needs elicitation requires human rapport and judgment
Confer with clients to determine needs.
#1736 · Core · 53% automatable
Advise client on interior design factors, such as space planning, layout and use of furnishings or equipment, and color coordination.
decision support — Layout planning aided; human owns design
Plan facility layouts or designs. Discuss designs or plans with clients.
#18519 · Core · 33% automatable
Coordinate with other professionals, such as contractors, architects, engineers, and plumbers, to ensure job success.
decision support — Coordination across trades needs on-site human execution
Coordinate construction or installation activities.
#18520 · Core · 66% automatable
Review and detail shop drawings for construction plans.
visual inspection — Technical drawing review aided, human verifies
Review details of technical drawings or specifications.
#20997 · Core · 22% automatable
Inspect construction work on site to ensure its adherence to the design plans.
visual inspection — Physical site verification against specs is human
Inspect facilities or sites to determine if they meet specifications or standards.
#1740 · Core · 45% automatable
Render design ideas in form of paste-ups or drawings.
visual inspection — AI aids illustrations; precise technical drawing human
Draw detailed or technical illustrations.
#1739 · Core · 33% automatable
Revision
Subcontract fabrication, installation, and arrangement of carpeting, fixtures, accessories, draperies, paint and wall coverings, art work, furniture, and related items.
decision support — Coordination across trades needs on-site human execution
Coordinate construction or installation activities.
#1737 · Core · 60% automatable
Select or design, and purchase furnishings, art work, and accessories.
data analysis — Materials inventory records and forecasting automatable
Select materials or props. Maintain inventories of materials, equipment, or products.
#1734 · Core · 53% automatable
Estimate material requirements and costs, and present design to client for approval.
data analysis — Project cost estimation from given parameters
Estimate costs for projects or productions. Present work to clients for approval.
#20999 · Core · 55% automatable
Research and explore the use of new materials, technologies, and products to incorporate into designs.
information retrieval — AI gathers references; creative synthesis is human
Conduct research to inform art, designs, or other work.
#20998 · Core · 55% automatable
Design spaces to be environmentally friendly, using sustainable, recycled materials when feasible.
decision support — AI proposes green features; engineer owns design decisions
Incorporate green features into the design of structures or facilities.
#1738 · Core · 45% automatable
Formulate environmental plan to be practical, esthetic, and conducive to intended purposes, such as raising productivity or selling merchandise.
data analysis — Evaluation aided; regulatory judgment and site data human
Monitor environmental impacts of production or development activities. Evaluate environmental impact of operational or development activities.
#1741 · Supplemental · 60% automatable
Plan and design interior environments for boats, planes, buses, trains, and other enclosed spaces.
text generation — Concepts generated; commercial curation human
Develop artistic or design concepts for decoration, exhibition, or commercial purposes.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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