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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Last Update: 5/19/2026
Your role’s AI Resilience Score is
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
High
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
High
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Very few data sources cover this career, or the available sources disagree significantly. Treat this score as a rough estimate.
Contributing sources
Textile, Apparel, and Furnishings Workers, All Other are somewhat more resilient to AI impacts than most occupations, according to our analysis of 3 sources.
Textile and apparel work has held up surprisingly well against automation because fabric is genuinely tricky for machines to handle — it bends, stretches, and bunches in unpredictable ways that robots still struggle with. The tasks that are hardest to automate, like custom alterations, creative design, quality judgment, and repair work where every piece is a little different, remain solidly human.
Read full analysisLearn more about how you can thrive in this position
Learn more about how you can thrive in this position
This role is mostly resilient
Textile and apparel work has held up surprisingly well against automation because fabric is genuinely tricky for machines to handle — it bends, stretches, and bunches in unpredictable ways that robots still struggle with. The tasks that are hardest to automate, like custom alterations, creative design, quality judgment, and repair work where every piece is a little different, remain solidly human.
Read full analysisAnalysis of Current AI Resilience
Textile, Apparel, Workers
Updated Quarterly • Last Update: 5/14/2026

If you sew, upholster, or finish fabric items for a living, you're working in a field that has stubbornly resisted full automation for decades — mostly because fabric is floppy. Robots are great at handling rigid metal parts, but soft cloth bends, stretches, and bunches in ways machines find hard to predict. That's finally starting to change.
The World Economic Forum reports that a new wave of "physical AI" [1] uses cameras and sensors in a "sense, think, act, learn" loop to manipulate fabric, catch defects in real time, and cut waste at the source — going beyond the older "cobot" approach where humans still had to align every piece. Industry-specific trade group SPESA highlighted ABB Robotics' OmniVance Sewing Cell [2], a fully automated SCARA-robot system that integrates fabric handling, feeding, inspection, and sewing for things like car interiors. The ARM Institute is funding U.S. projects [3] like Sewbo's robotic apparel work, partly because manual sewing puts workers in uncomfortable, sometimes risky conditions.
And startups like unspun are bringing in AI-enabled 3D weaving that turns dozens of cut-and-sew steps into one automated process [4], backed by Walmart and REI.

Adoption is happening, but unevenly. On the "fast" side, fashion companies are racing to apply AI: California Apparel News notes that in 2026, AI has become "central to progress" [5] for forecasting, inventory, and production, with leaders aiming for "faster execution with fewer people." On the "slow" side, hands-on sewing and upholstery are harder to replace: ARM Institute notes 97% of U.S. clothing is still imported [3], so cheap overseas labor often beats expensive robotics on cost. The good news for you: re-shoring efforts need humans to operate, maintain, and supervise these new machines, and skills like creative design, custom alterations, quality judgment, and repair work — where every piece is a little different — remain genuinely hard for AI to copy.
Staying curious about new tools is your best move.

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They create and repair clothes, furniture, and other fabric items by cutting, sewing, and assembling materials to meet specific designs and needs.
Median Wage
$37,010
Jobs (2024)
14,700
Growth (2024-34)
-9.4%
Annual Openings
1,700
Education
High school diploma or equivalent
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034

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