The Future Of Fashion

A look at the evolution of the fashion industry and where technology is taking it next, from AR/VR dressing rooms to temperature-changing fabrics and beyond.

Fashion has always been a hotbed for innovation — from the invention of the sewing machine to the rise of e-commerce. Like tech, fashion is forward-looking and cyclical.

It’s also a huge industry. The ~$2.4T fashion sector is one of the largest industries in the global economy.

And today, tech is transforming fashion at a faster pace than ever.

From robots that sew and cut fabric, to AI algorithms that predict style trends, to VR mirrors in dressing rooms, technology is automating, personalizing, and speeding up every aspect of fashion.

Product Design

Tech is automating the fashion designer. 

Fashion brands of all sizes and specialties are using technology to understand customers better than ever before.

Project Muse

As those data collection efforts grow more sophisticated, artificial intelligence will reshape brands’ approach to product design and development, with a focus on predicting what customers will want to wear next.

AI Becomes The Designer

Google has already tested the waters of user-driven AI fashion design with Project Muze, an experiment it deployed in partnership with German fashion platform Zalando.

The project trained a neural network to understand colors, textures, style preferences, and other “aesthetic parameters,” derived from Google’s Fashion Trends Report as well as design and trend data sourced by Zalando.

From there, Project Muze used an algorithm to create designs based on users’ interests and alignment with the style preferences recognized by the network.

Amazon is innovating in this area as well. One Amazon project, led by Israel-based researchers, would use machine learning to assess whether an item is “stylish” or not.

Another, out of Amazon’s Lab126 R&D arm in California, would use images to learn about a particular fashion style and create similar images from scratch.

If that sounds like “fast fashion by Amazon,” that’s because it probably is. The e-commerce giant has also patented a manufacturing system to support on-demand apparel-making. The tech could be used to support its Amazon Essentials line or the suppliers in Amazon’s logistics network.

Of course, the outcomes of human-free AI design aren’t always runway-ready. Many designs created for users of Google’s Project Muse were just unwearable scrawls and scribbles, while some reports on the Amazon Lab126 initiative called the design results “crude.”

But the gap between AI-developed designs and human-made ones is closing. In April 2019, an AI “Designer” called DeepVogue placed second overall and won the People’s Choice Award at China’s International Fashion Design Innovation competition. The system, designed by Chinese technology firm Shenlan Technology, uses “deep learning” to produce original designs drawn from images, themes, and keywords imported by human designers.

Clearly, much more R&D is needed before brands rely on AI-only designers. But artificial intelligence is already helping brands create and iterate their designs more quickly.

AI Is Already Influencing Fashion Brands

In 2018, Tommy Hilfiger announced a partnership with IBM and the Fashion Institute of Technology. The project, known as “Reimagine Retail,” used IBM AI tools to decipher:

  • Real-time fashion industry trends
  • Customer sentiment around Tommy Hilfiger products and runway images
  • Resurfacing themes in trending patterns, silhouettes, colors, and styles

Knowledge from the AI system was then served back to human designers, who could then use it to make informed design decisions for their next collection.

“Reimagine Retail was a powerful example of what happens when fashion partners with a global tech leader to advance challenging innovations” – Michael Ferraro, director of the FIT/Infor DTech Lab.

Stitch Fix is already at the forefront of AI-driven fashion with its “Hybrid Design” garments, which are created by algorithms that identify trends and styles missing from the Stitch Fix inventory and suggest new designs — based on combinations of consumers’ favorite colors, patterns, and textiles — for human designers’ approval.

The company details how it works (shown below) in the “Algorithms Tour” on its website.

Stitch Fix has developed over 30 pieces of apparel using the Hybrid Design methodology.

The company has said that the AI-designed pieces perform comparably in “keeper” sales to the garments from its fashion-brand suppliers. That’s likely because Stitch Fix has such vast troves of customer data informing its AI, thanks to its subscription-based, feedback-focused business model

“We’re uniquely suited to do this,” said Eric Colson, Chief Algorithms Officer at Stitch Fix. “This didn’t exist before because the necessary data didn’t exist. A Nordstrom doesn’t have this type of data because people try things on in the fitting room, and you don’t know what they didn’t buy or why. We have this access to great data and we can do a lot with it.”

Design isn’t the only area where Stitch Fix is putting AI and machine learning initiatives to work. The company employs a team of more than 85 data scientists to oversee machine learning algorithms that are used to inform everything from client styling to logistics to inventory management.

According to Colson, the company is already seeing ROI from its AI investments, including increased revenue, decreased costs, and improved customer satisfaction.

As more and more AI “assistance” programs advance, they will help brands make smarter strategic decisions around product development and new business lines.

3D design platforms like CLO (shown below) also make it easy to tweak designs on the fly. This means brands can already use real-time AI insights to modify fashions right up to the minute they hit production.

Below, we illustrate how tech is automating away the fashion designer, as styles become more personalized and influenced by digital signals.

Similar to Amazon’s Lab 126 initiative & Google’s Project Muze, scientists from UC San Diego and Adobe have outlined a way for AI to learn an individual’s style and create customized computer-generated images of new items that fit that style.

The system could enable brands to create personalized clothing for a person based solely on their engagement with visual content.

At a more macro level, it could also allow a brand to predict broader fashion trends based on historical data from its entire user base. The predictions could ultimately be used to guide the design of a product or an entire label.

Excerpt from “Visually-Aware Fashion Recommendation and Design with Generative Image Models”

The next era of fashion is all about personalization and prediction. With more and more data, algorithms will become trend hunters — predicting (and designing) what’s next in ways that have never been possible.

True Fit, for example, closed a $55M Series C round in 2018 to bring its funding to $102M. The company’s big data platform facilitates capabilities like AI-powered fashion discovery and exact-fit clothing and shoe recommendations.

With over 100 million registered users, the platform uses transaction data to determine customer preferences that “better personalize all touchpoints of the consumer journey” for brands, according True Fit CEO William R. Adler.

Another company capitalizing on the smart fitting, Virtusize, enables online shoppers to buy the right size, either measuring the clothes in their closet or by comparing specific brands and styles to their own.

Virtusize claims that, by removing uncertainty around size and fit, it can increase average order values by 20% and decrease return rates by 30%. The Japan-based company counts Balenciaga and Land’s End among its clients, as well as Zalora — a leading online fashion store in Asia.

Increasingly, consumer preferences will guide every aspect of the design and production process.

Platforms like True Fit may help identify the types of materials shoppers prefer, or even pinpoint how important sourcing and manufacturing conditions are to a unique shopper.


Fast fashion has created an instant gratification mentality. 

Since WW2, fashion has officially been broken up into seasons: spring/summer lines debut on runways in early fall, and autumn/winter lines debut in February.

The staggered timeline is designed to give brands enough time to gauge the interest of retail buyers and customers. In the time between when fashions are introduced and when they arrive on store shelves, brands assess demand so that they can manufacture the right number of garments for the season.

Fast fashion, in which designs move quickly from catwalk to store shelves, has upended every aspect of that model.

Brands like Zara, H&M, Top Shop, and Forever 21 have built their businesses on speed and agility. Once these retailers spot a new trend, they can deploy their hyper-rapid design and supply chain systems to bring the trend to market as quickly as possible.

This allows fast fashion brands to beat traditional labels to market. Garments and accessories strutted down runways in September and February may get spotted and replicated by fast-fashion brands before the originals even hit stores.

With a nearly real-time ability to get the newest styles on shelves, fast fashion brands can also push out broader varieties of clothing styles to cater to the preferences of smaller, more targeted segments of customers.

They can also push smaller runs to test the waters for customer demand, or sell collections for hyper-short lifespans.

The rise of fast fashion is decimating the biannual seasonality that has long structured the fashion industry.

Fast fashion brands may issue as many as 52 weekly “micro-seasons” per year. Topshop, for example, introduces ~400 styles per week on its website.

To keep up, traditional apparel brands are now debuting around 11 seasons a year.

Cheap alternatives to high-fashion items remain hot consumer commodities. Even amid the retail slowdown, Zara’s parent company, Spanish retail giant Inditex, saw nearly $30B in sales in FY18 (February 2018 – January 2019) — a 3% increase in net sales.

Social media accelerates that cycle. Influencer marketing and other social media strategies help new trends travel fast, creating rapid consumer demand for hyper-cheap fashions.

Shoppers act on that demand instantly, thanks to “See-Now Buy-Now” tools on platforms like Instagram and Pinterest.

Fashion Nova is one example of a fast fashion e-commerce brand that has successfully leveraged social media to build its customer base and its brand. The company has more than 15 million followers on Instagram, as well as more than 3,000 influencers, known as #NovaBabes, promoting its clothes.

Fast fashion brand Boohoo has said that its profits doubled after paying celebrities to promote its products on Instagram to 16- to 24-year-old fans.

Yet fast fashion clearly has a dark side. Brands manufacture low-cost, low-quality apparel in factories with questionable working conditions, relying on workers who receive low pay. The inexpensive materials used to create cheap garments are also laden with chemicals.

Since rapid production runs create excessive textile waste, cheaply made apparel harms both factory workers and the environment: according to the Environmental Protection Agency, some 12.8M tons of clothing is sent to landfills annually. Global textile production emits 1.2 billion tons of greenhouse gases annually (more than international flights and maritime shipping combined). The fashion industry is responsible for up to 10% of global CO2 emissions, 20% of the world’s industrial wastewater, 24% of insecticides, and 11% of pesticides used, according to some estimates.

While the sustainability issues within fashion, and fast fashion in particular, are not new, what is new is how the industry’s most influential customers are starting to respond.

The Push for Sustainability

Consumers are wising up to the negatives of fast fashion: socially conscious shoppers are embracing the growing movement of “slow fashion,” which focuses on sustainable materials and transparent, ethical labor and manufacturing.

In 2018, the fashion search engine Lyst tracked more than 100 million searches on its shopping site and reported a 47% increase in shoppers looking for products with ethical and style qualifications, including terms such as “vegan leather” and “organic cotton.”

The growing concern about sustainability is particularly prominent among younger generations: 83% of millennials in the United States value companies implementing programs to improve the environment, according to The Conference Board Global Consumer Confidence Survey. And 75% are willing to change consumption habits for more sustainable offerings.

Young, upcoming brands in the fashion space are making moves to align with this shift in consumer sensitivities. Cuyana urges customers to shift their focus to buying “fewer, better things.” Its products are made with sustainable, plant-based materials including linen and silk. Another young company called Pact offers cotton garments that are certified organic by GOTS (Global Organic Textile Standard).

The shift to sustainability is particularly noticeable in the shoe industry. Allbirds, for example, produces shoes made from eucalyptus leaves.

In response, a number of prominent brands have announced new clothing lines and initiatives focused on sustainable materials:

  • H&M’s Conscious Collection features a leather jacket and cowboy boots made using Piñatex, a leather-like material made from pineapple leaves which are typically discarded in pineapple production. The line supports H&M’s broader goal to increase the use of sustainable resources to 100% by 2030.
  • Levi’s Wellthread x Outerknown collection is piloting products with 30% “cottonized” hemp and jackets with detachable hardware to make them more easily recyclable. The company’s Water<Less(R) Denim line was created to reduce the amount of water used in producing some of the brand’s most popular styles and fits.
  • Adidas has announced plans to make 11 million pairs of sneakers with recycled ocean plastic in 2019.
  • Online resale site thredUP teamed up with Conscious Commerce to launch the Choose Used Capsule Collection, a limited edition collection of secondhand pieces screen-printed with fresh designs.

A shift to more sustainable fabrics is not the only way the fashion industry is shifting to embrace more sustainable practices.

ThredUp bills itself as “the largest online consignment and thrift store.” The company predicts that the total secondhand apparel market (resale + thrift & donations) will hit $51B by 2023 — driven by a growth in the resale sector.

Another company, Poshmark, takes a marketplace approach to fashion, allowing customers to buy and sell used items with other users through the site.

Taking a cue from these younger companies, H&M announced (in April 2019) that it will test sales of secondhand and vintage items in a bid to boost the brand’s sustainability cred and connect with environmentally minded customers.

AI and advanced technologies may also have a part to play in the push for sustainability in fashion.

One area they could improve is returns, which is currently a significant source of waste within the fashion industry (and the e-commerce segment in particular). On average, 40% of online purchases are returned. With data and AI capabilities, retailers could more effectively match customers’ shopping behavior and preferences, potentially reducing the overall number of returns.

Even as the slow fashion movement gains traction, the rise of social media and the fast fashion model (not to mention e-commerce) have transformed fashion as we know it.


The costs of starting a fashion brand have gone down significantly, thanks to technology and e-commerce.

The dawn of Etsy made it easy for anyone to start an online shop and build a following. Now, decreased production costs make it feasible for small or emerging brands to manufacture small runs of products at reasonable margins and build up online audiences from there.

In years past, fashion labels would have to manufacture hundreds or thousands of items in order to produce them at a reasonable price.

Now, startups like Maker’s Row make it simple for small labels to find small-batch manufacturing partners that can meet their needs at scale, with transparent standards around pricing and sourcing. Emerging brands can weave small-batch runs (and transparent production standards) into their marketing.

NYC-based menswear line Noah, for example, produces ultra-small batch clothing lines — rumored to sometimes be as little as 12 or 24 items — and often sell out of these items quickly. The launches includes detailed blog posts about the items’ sourcing and purpose.

Large high-end brands are also evolving their approach to production to better compete with fast fashion retailers.

Tommy Hilfiger makes the fashions in its new TommyNow line available instantly — all around the world, in-store and online — as soon as they sashay down the runway.

That means TommyNow items hit stores three times faster than traditional collections, with just a 6-month window between product ideation/design and release.

“It’s about delivering on the instant gratification that consumers are really seeking,” says Avery K. Baker, Chief Brand Officer at Tommy Hilfiger. “Closing that gap between the visibility of a fashion show and the moment of purchase.”

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