Leah McClure, Co-Founder and CEO of Rotostitch.
Walk into a modern semiconductor factory and you’ll see full end-to-end automated processes. Visit an automotive plant and you’ll watch lines weld and paint without a human touch. But walk into a modern apparel factory, and you’ll still find rows and rows of people guiding fabric manually through a sewing machine, one seam at a time.
For all our progress in robotics, AI and advanced manufacturing, textiles remain stubbornly manual in many areas including sewing. This isn’t due to lack of need. It’s a combination of technical difficulty, underinvestment and neglect. Textiles bundle some extremely difficult engineering problems: deformable materials, complex 3D shaping and quality requirements that are both structural and aesthetic.
Underpinning all of this is a manual supply chain that forces brands to either sacrifice quality for “on-demand” speed or place bulk orders months early and dump the unsold inventory. The payoff for solving this is huge: over $500 billion is lost each year due to apparel discarded by brands due to overproduction.
While some believe the answer is better forecasting, consumer demand is too volatile. I believe that process and machinery automation that collapses lead times, enables smaller lots and aligns output to real-time demand is what can help address this challenge.
Textiles: Once A Frontier Of Automation
It’s easy to forget that textiles were once the hotbed of manufacturing innovation. The industry has received major automation attention before. The stocking-frame knitting machine from 1589 is considered the first mechanization of knitting and helped shift apparel from a hand craft towards large-scale factory production. The Jacquard punchcard loom from 1804 automated complex pattern weaving and its punchcards even inspired early programming.
By the mid 1800s, sewing machines transformed how garments were assembled, compressing hours of hand stitching into minutes of foot-powered precision. In one case in France, the invention of an early sewing machine caused tailors to fear the loss of their jobs so intensely that they rioted and destroyed the inventor’s machines.
Why Textiles Lagged While Everything Else Leaped Ahead
Textiles and relevant machinery is rarely covered in engineering curricula today. I believe there has been an apparent loss of interest, loss of mentors and loss of education. As a consequence, there is less competition, less creativity and less talent tackling the hardest technical problems within the industry.
In my opinion, textile interest has recently skewed stereotypically female while automation and manufacturing skewed stereotypically male. This is a divide that left few engineers able to speak both languages.
Moreover, cheap labor has masked the technical debt. It is a common opinion that offshoring has slowed innovation. While this may or may not be true for many industries, offshoring made the manual status quo in textiles look “good enough” for decades, delaying investment in difficult automation and fragmenting the supply chain. As demand volatility rises, brands are now re-examining near-shoring and new automation solutions to gain speed and resilience.
The Silver Lining: The Hidden Talent Pool Powering Textile Automation
Although the industry is facing many challenges, there are signs that changes are occurring. Cross-domain talent is emerging within manufacturing, automation and textiles. There is a specific niche of engineers who understand all the fundamentals. Passion for these overlapping fields seems to be increasing. This convergence of skills, long missing in textiles, is beginning to unlock previously unsolved automation bottlenecks.
Market pressure is also rising and I believe this will help to drive new talent to the area. The EU has introduced a ban on the destruction of unsold apparel by July 2026. Brands can no longer afford to over-order months in advance and then dump their excess inventory. Forecasting will never be the answer as consumer demand is constantly changing. What’s needed is near-on-demand production while maintaining a high quality, and that requires new process and machinery automation.
How To Harness The Talent: Strategies For Building Breakthrough Teams
Companies should prioritize rapid iteration over perfection and embrace fast discovery of failure points. Failures will inevitably occur, so it is important to discover them as soon as possible.
Invest in mentorship networks, even if the “perfect” mentor doesn’t exist. For instance, a manufacturing humanoid startup should seek guidance across previous successful startups, manufacturing companies and general robotics even if not many people exist with expertise in all three.
If no one sees the full picture yet, everyone should create it themselves. In industries like textile automation, that’s not a flaw; it’s an opportunity. Companies should always empower individuals within a team to speak up and innovate wherever the opportunity arises.
Lessons Engineers In Any Industry Can Learn From Textiles
Look for neglected, high-need niches. I believe that if you want to find the next frontier of innovation, follow the hard problems everyone else forgot about. Even if a role doesn’t sit inside a high-need niche, these same habits still pay off. Everyone should look for problems they are capable of solving for. Innovation is a transferable muscle and should be improved upon whenever possible.
Textiles are proving that even century-old industries can leap forward when interdisciplinary talent, special attention and new company cultures converge. No matter the industry, the playbook is the same: prototype iteratively, prioritize learning, empower all contributors within a team and look for cross-domain talent with insight into multiple industries.
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