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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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The AI Resilience Report is a project from CareerVillage®, a registered 501(c)(3) nonprofit.
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%).
Med
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.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
Tailors, Dressmakers, and Custom Sewers are somewhat more resilient to AI impacts than most occupations, according to our analysis of 7 sources.
Tailoring is labeled "Mostly Resilient" because the hands-on, physical skill at the heart of this work — reading a real human body and shaping fabric to fit it perfectly — is still something machines genuinely struggle to do. Fabric is floppy and unpredictable, every body is different, and that combination makes robotic sewing slow to advance, keeping skilled human hands in high demand.
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
Tailoring is labeled "Mostly Resilient" because the hands-on, physical skill at the heart of this work — reading a real human body and shaping fabric to fit it perfectly — is still something machines genuinely struggle to do. Fabric is floppy and unpredictable, every body is different, and that combination makes robotic sewing slow to advance, keeping skilled human hands in high demand.
Read full analysisAnalysis of Current AI Resilience
Tailors and Dressmakers
Updated Quarterly • Last Update: 5/14/2026

If you love sewing, here's some good news: the most hands-on parts of tailoring are still very hard for machines to copy. AI is mostly being used to help tailors right now, not replace them. At the Fashion Institute of Technology, professor Leigh LaVange built a winning project called "Automated Custom Sizing" that uses 3D technology and AI to produce custom-tailored clothing on demand for all body types, with an AI program that determines necessary adjustments to the pattern based on the customer's specifications and critical fit points, like the waist, while preserving the original design.
Meanwhile, factory-side robotic sewing is advancing slowly — the ARM Institute and Sewbo recently demonstrated processes needed to perform half of the labor that goes into a pair of jeans by automating tricky operations like side seams and front and back rises that have traditionally relied on skilled manual labor due to the complexity of fabric behavior. Some companies are even sidestepping sewing entirely with adhesives and robotic arms [1]. Still, as veteran Manhattan tailor Kil Bae put it, artificial intelligence is automating pattern making but so far can't replicate a tailor's handiwork — different bodies have different shapes that machines struggle to read.

Adoption in custom tailoring is moving slowly, and that's mostly about economics and physics. Fabric is floppy, three-dimensional, and unpredictable, which is exactly what robots find hardest. McKinsey's State of Fashion 2026 notes that while global fashion and luxury players have made progress deploying automation with generative AI in select functions for routine tasks, the biggest gains are in marketing, design, and back-office work — not in physically handling garments [2].
California Apparel News reports [3] that brands are now embedding AI into everyday workflows like forecasting and pattern development rather than replacing the people who stitch. Labor conditions also discourage replacement: fewer than 17,000 tailors, custom sewers and dressmakers were working in business establishments nationwide, a 30% decline from a decade earlier, and the median age was 54 last year, 12 years older than the median for the entire employed population. Demand is actually rising — Nordstrom, North America's largest employer of tailors, teamed up with the Fashion Institute of Technology to launch a nine-week program in advanced sewing, and customarily, tailoring has never been part of the American skill set.
Cost is another barrier: industrial sewing robots are expensive, and small alteration shops can't justify them. So if you're curious about this craft, AI is more likely to become your assistant — helping with measurements, patterns, and design ideas — than your competition.

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They design and create clothes by measuring, cutting, and sewing fabric to fit people perfectly and match their style.
Median Wage
$40,860
Jobs (2024)
38,800
Growth (2024-34)
-4.5%
Annual Openings
5,000
Education
No formal educational credential
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
Press garments, using hand irons or pressing machines.
Sew garments, using needles and thread or sewing machines.
Let out or take in seams in suits and other garments to improve fit.
Maintain garment drape and proportions as alterations are performed.
Take up or let down hems to shorten or lengthen garment parts such as sleeves.
Assemble garment parts and join parts with basting stitches, using needles and thread or sewing machines.
Remove stitches from garments to be altered, using rippers or razor blades.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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