Introduction
Let’s take a trip down memory lane.
Back in the day, my grandfather owned one coat. Just one.
And he took care of it like it was a prized possession. If it tore, he’d take it to the local tailor.
Can’t imagine it, right? Yup…me too.
No matter how much I love how technology is evolving, something about old-school ways just sits right with my soul. I’ve always enjoyed talking to my grandparents — luckily, they have endless stories. But one recent chat with my grandad really stuck with me.
He told me about getting his first winter coat in high school. And I was like, Wait, you didn’t have your own coat before that? But back then, things were different. No fast fashion, no endless shopping options — just a few quality pieces that you took care of because replacing them wasn’t so easy. He didn’t have a closet full of clothes, so he made sure the ones he had lasted.
And it wasn’t just the coat. He also had only one umbrella. And when it broke, he didn’t toss it and buy a new one — he took it to a guy whose whole job was fixing umbrellas. Can you imagine? A craftsman dedicated just to repairing umbrellas.
Everything was slower. Fewer stores, fewer options, more care.
Fast forward to today, and we’re drowning in a sea of clothes. We live in a world of consumerism, where everything is available, everything is cheap, and everything is disposable.
The average person buys 60% more clothing than they did 15 years ago (and let’s not even talk about 50–60 years ago when my grandpa was a teenager). Back then, people owned fewer clothes, but they valued them more. They repaired, reused, and made things last.
Now? According to statistics, we wear something an average of seven times before moving on. Clothing production has doubled in the last two decades, and yet, 85% of all textiles still end up in landfills each year. That’s about 92 million tons of waste globally — most of it barely worn. Fast fashion sure has its dark side.
Wait.. I am getting to the point 🙂
It is … while we’re busy buying clothes we’ll wear few times, there are still millions of women manually stitching garments for hours on end, often for less than a living wage. Craftsmanship? It’s fading. Manual labor? Underpaid. And yet, the fashion industry is worth over $2.5 trillion globally. So, what if AI could step in and change the game? What if it could help bridge the gap between overconsumption and underpaid labor?
Let’s explore.
A brief history of fashion manufacturing
Fashion manufacturing wasn’t always this chaotic. In the early 20th century, clothing was made by skilled artisans who took pride in their work. A single tailor could spend weeks crafting a bespoke suit, and people valued their garments because they were expensive and hard to come by. Fast forward to the 1980s, and the rise of fast fashion changed everything. Brands like Zara and H&M made trendy clothing affordable and accessible, but at a cost: exploitative labor practices, environmental degradation, and a culture of disposability.
Today, the fashion industry is one of the largest polluters in the world, responsible for 10% of global carbon emissions and 20% of wastewater. And yet, we keep buying. The average American throws away 81 pounds of clothing every year. Meanwhile, in developing countries, women work 14-hour days in unsafe conditions for less than $3 a day.
It’s a broken system, and it’s time for a change.
How AI can help fashion manufacturing
Automating repetitive tasks
AI-powered robots are already making waves in fashion manufacturing. Companies like Sewbo and SoftWear Automation have developed robots that can sew garments with precision and speed. These machines use computer vision and machine learning to handle tasks like cutting fabric, stitching seams, and even embroidering designs.
How does it work? AI agents analyze patterns and fabrics, then guide robotic arms to perform tasks with millimeter accuracy.
Cost comparison: While the initial investment in AI-powered robots can be high (up to $100,000 per machine), they can reduce labor costs by up to 50% in the long run.
Who does it better? Robots excel at repetitive tasks, but humans are still needed.
Example: Adidas’ Speedfactory uses robots to produce shoes in just a few hours, cutting production time from weeks to days.
Predictive analytics for demand forecasting
AI can analyze data from social media, weather patterns, and past sales to predict what consumers will want next season. Platforms like Heuritech and Edited use machine learning to analyze millions of data points and provide brands with actionable insights.
How does it work? AI agents scrape social media for trending colors, styles, and patterns, then predict which items will sell best.
Cost comparison: Implementing AI analytics can cost between 10,000 and 50,000 annually, but it can reduce overproduction by up to 30%.
Who does it better? AI is faster and more accurate than human analysts, but humans are still needed to interpret the data and make strategic decisions.
Example: H&M uses AI to analyze store returns and customer feedback, helping them design clothes that people actually want to keep.
Personalized fashion at scale
AI is making it possible to create custom clothing at scale. Platforms like Unmade and Zozotown use AI to let customers design their own garments, which are then produced on-demand.
How does it work? AI agents use algorithms to generate patterns and adjust designs based on customer input.
Cost comparison: On-demand production reduces waste and inventory costs, but it requires a significant upfront investment in AI technology.
Who does it better? AI can handle the technical aspects of customization, but humans are needed to ensure quality and fit.
Example: Nike’s Nike By You platform lets customers design their own sneakers, which are then produced using AI-driven manufacturing processes.
Ethical production monitoring
AI can help ensure that factories adhere to ethical labor practices. Companies like Tailor Technologies and Provenance use blockchain and AI to monitor supply chains and ensure transparency.
How does it work? AI agents track every step of the production process, from raw materials to finished products, and flag any violations.
Cost comparison: Implementing ethical monitoring systems can cost between 5,000 and 20,000 per factory, but it can improve brand reputation and customer loyalty.
Who does it better? AI is more efficient at tracking data, but humans are needed to address issues and enforce standards.
Example: Patagonia uses AI to monitor its supply chain and ensure fair wages and safe working conditions for its workers.
Sustainable material innovation
AI is helping create new, eco-friendly materials that reduce the fashion industry’s environmental impact. Companies like Bolt Threads and MycoWorks use AI to engineer materials like mushroom leather and spider silk.
How does it work? AI agents analyze molecular structures and simulate material properties to create sustainable alternatives.
Cost comparison: Developing new materials can be expensive, but it can reduce long-term costs by minimizing reliance on harmful resources.
Who does it better? AI accelerates the R&D process, but humans are needed to test and refine the materials.
Example: Stella McCartney has partnered with Bolt Threads to create a line of clothing made from mushroom leather.
Will fashion founders accept AI?
Fashion founders are a unique breed. They’re creative, visionary, and often resistant to change. They can tend to fall into three camps when it comes to AI:
The Early Adopters: These are the ones already thinking ahead. They know that people today care more about sustainability, ethical production, and reducing waste. AI helps them do exactly that — cut excess inventory, optimize materials, and make fashion more eco-friendly. For them, AI isn’t a replacement for creativity; it’s a way to build a smarter, more responsible industry.
The Skeptics: The artists, the purists, the ones who see fashion as a deeply human craft. They fear AI will turn the design into a numbers game, taking away the soul of their work. But let’s be real — fashion has always evolved with technology. AI won’t replace creativity, but it will change how things are made. The real challenge is finding the balance.
The Realists: The big fashion houses. For them, it’s simple — if AI can lower costs and boost profits, they’re on board. Not for the love of tech, but because efficiency and margins always win. If AI can predict trends, reduce waste, and speed up production, they’ll use it. If not, they won’t.
One thing is certain: AI isn’t waiting for approval. It is already making its mark on the industry. The only question is — who’s adapting, and who’s getting left behind?
Where do we go from here?
Fashion is at a turning point. We can keep feeding the cycle of overproduction, waste, and cheap labor — or we can start doing things differently. AI isn’t some magical fix, but it can be a tool to help everyone slow down, waste less, and rethink how things are made.
It would be nice to have a world where clothes are designed to last, made ethically, and actually valued by the people who wear them. But for that to happen, we need to start questioning our habits. Next time you’re about to buy something, maybe take a second and ask: Do I really need this? If the answer is no… well, you know what to do.
Because the future of fashion isn’t just about what we wear — it’s about how it’s made, who makes it, and what kind of world we want to live in.
AI can help us get there — but only if we let it. And maybe one day instead of “Made in China, Bangladesh, or Vietnam,” we might see “Made by AI” on clothing labels. And at the rate things are going, that day might not be too far off. AI-powered factories are already on the rise, promising high-quality, sustainable fashion at scale.
Interested to learn more about AI? Do not miss our previous blogs!
