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“We will move from Mobile-First to AI-First.” CEO Sundar Pichai, February 2016.

“As consumers, we started our awareness of computers with desktops,” explains , London-based technologist, evangelist, and lead solution architect EMEA. “We then moved to laptops, and onto smart mobile devices, and subsequently to the Cloud. Now we’re moving to Gen.AI.”

creates new original content based on text, images, audio, and 3D models.

With the November 2022 launch of , a virtual assistant/chatbot developed by and , the world suddenly seems to be concerned about AI taking over, causing job loss, as we know it. And the fashion industry has not been immune to these concerns.

While AI actually started in the 1950s, it’s the that have peaked industry interest and sallied fears.

The premise of AI is simple: feed the computer, don’t code it. Through , allow the system to recognize and organize input.

“AI is a good technology to detect patterns quickly, something that takes a human a long time to do,” Domingos says. “Gen.Ai can help fuel the creative process. With a lot of data Gen.AI can be good at predicting trends, and help create more diverse products.”

At the March 2024��, Steve Brown, International Markets Merchandising��, walked the audience through the brand’s AI journey to create range plans. “We will spend three hours in a conference room talking about how we feel about a sweater,” he explains. “With clear insights from AI, we can now back that emotion up with facts.”

Anna Franziska Michel was a fashion designer who was heading toward burnout from creating rapid collections one after the other. She founded and created Berlin-based as a way to ease repetitive tasks that have nothing to do with creativity, explains Yoona CMO Laura Jimenez Ruiz. “Inspired by a catwalk done in collaboration with Microsoft 10 years ago, she started writing code. In 2020 she officially launched Yoona.”

“More than 70% of carbon footprint from products is determined at the design stage, with designers working manually. And in enterprise fashion, 70% of products made are not sold. Design is by hope. Anna sees tech as the solution to both of these problems,” Ruiz explains.

“By analyzing performance data (the brand’s best sellers), competitor’s data, and trend data (catwalk analysis) we eliminate hope. We provide one click to designs, color pallets, even prints,” she says. “We are different because designs are unique based on your company’s data, your competitors’ data, and the trend data you choose. Our Gen.AI designs are tailored to your brand.”

“The system accepts numbers, images, any type of data,” Ruiz explains. “Some clients give us pictures; some give us excel sheets with 20 years of data. Our biggest asset is using the brand’s data, and no brand data is the same. Of course, the data remains the client’s. And the more data you give to the system, the better the result,” she says.

“The system constantly crawls—24 hours— to get fashion data. And for our clients, we pull competitor data that is relevant to each region. India is different from Europe which is different from South Africa,” she adds.

Yoona has more than 7300 users globally, and clients include , , r, as well as sustainable brands , and Accessories.

�۴ǴDzԲ�’s ��report boasts��reducing product development costs by as much as 90% and increasing speed to market by 87%.

“We are not only solving the commercial problem brands have today. But we are also solving the sustainability problem the industry faces today. We’ve seen CO₂ emissions reduced up to 93%,” says Ruiz.

“It’s like having a conversation with my showroom manager, or my department store buyers,” explains Bunny Donahue, creative director of , UK-based fashion house specializing in clothing for those living with disability. With more than 30 years industry experience (, ) Donahue isn’t afraid that Gen.AI will eliminate her job, or take away design creativity.

“If anything, Gen.AI helps creatives focus on designing the right product. We are a visual industry. How can having realistic product visuals with compelling sales, trend, and consumer data NOT be helpful?”

Donahue has worked with , a NY-based Gen.AI platform, to create realistic renders of Differently Enabled dresses for clients to see before product development begins.

According to Kenna AI co-founder Meir Erani, the platform was developed exclusively for the fashion industry, allowing users to go from black-and-white sketches to realistically rendered images in minutes. With more than 30 years industry experience, Erani understands the needs stylists, merchandisers, and designers have for product and print ideation.

“We are a front-end tool, not production,” he explains. “But the E-commerce teams find it useful to create backdrops for photo shoots.”

Alexandra Serban, Bucharest-based AI fashion artist and brand ambassador for Kenna AI, recently used the platform for her entries in , as well as generating content for her fashion work. Through Kenna AI she created backdrops, garments, even models.

, US-based fashion industry creative consultant and digital guru, says merchandisers are seeing Gen.AI as a fantastic tool.

“In the late 1990s, I texture mapped a pair of Bermuda Shorts for the cover of a catalogue. It was a proof of concept then for how simulated garments could be presented to consumers before product creation. It took me an entire day to create that artwork. Today, Kenna.AI takes less than a minute.”

Serban uses multiple AI tools and is also a brand ambassador for , a Delaware-based AI solution provider that offers brands and designers the opportunity to create and curate fashion lines incorporating trend insights and leveraging data on best-selling styles.

But the application of Gen.AI is not limited to creatives.

As part of the startup acceleration program at , Refabric plans to expand technology offerings to include production, e-commerce, and content marketing solutions. Refabric’s clients include , , and Turkish manufacturer

By training AI to understand chemistry, and the context of those chemicals being used to create fabrics, Gen.AI can be helpful in solving sustainability problems through innovative answers to the fashion industry’s challenges, Domingos explains.

“Here are a bunch of chemicals. Here are the results of our existing tests. Here’s a potential new material with those chemicals. What can we expect?” Domingos offers as an example.

“How can we use less water? How will we treat the water [that] we do use to be non-polluting? How do we reduce waste, or how do we reduce plastics in the water table? How can we mass produce colors that will be less harmful to people and the planet? These are all opportunities for Gen.AI,” he says.

“If a brand has good data on what worked and what didn’t work in production, then Gen.AI has the potential to predict R&D outcomes,” he explains.

Gen.AI remains experimental.

The (machine learning modules that analyze massive data sets of language to generate text and imagery) that Gen.AI currently operates on, is not industry-specific.

&/aatccnews_2024_08a/8220;We have all of the world’s knowledge in large language model, but we currently have one big model. At Hitachi, we are working with the financial industry to develop their specific industry’s language. This will be the case of all industries—shrink the world’s knowledge to my specific industry: retail, textiles, apparel, footwear—in essence, moving from Large Langue Models to Small Large Language Models,” Domingos explains.

“I see so much AI-generated content that all sounds the same,” says Anne Slowey, celebrity speech writer, former fashion news director fashion tech evangelist, and adviser to fashion tech start-ups.. “Specificity of language and syntax are what distinguish the human experience as rare and will always resonate with the most power and impact,” she explains. “It is important to train Gen.AI on the fashion language we actually use. Gen.AI is only as good as what we teach it.”

“We are still figuring out exactly what we want to do with it,” Domingos concludes. “To drive improvements brands should be involved sooner rather than later.”

Erani agrees. “AI is on everyone’s tongue, and it is a work in progress for fashion. Sustainable enough to try, but where it will land is still somewhat unknown. The wow factor does dissipate when we start asking ‘who in my organization is going to use it?’ My advice? Anyone who embraces tech as part of their workflow needs to be involved. Just kick the tires and play with it.”

“Getting started is not as hard as you might think,” explains Mark Williams, Hitachi Digital Services senior director and head of retail, hospitality, and travel EMEA. “A day workshop to understand how ready your brand is, followed by a few days of brainstorming business opportunities with Gen.AI, is all it takes to begin a pilot. In some cases, in less than a month after that we can begin full deployment.&/aatccnews_2024_08a/8221;

Images Courtesy Differently Enabled and Kenna AI.�� Two flat sketches realistically rendered based on fabric input.�� Models,�� backgrounds, and lighting also generated via Kenna AI.

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Craig Crawford is a two-time Tabbie award winning author and founderprenuer of Crawford IT, () a London-based consulting firm specializing in the digital transformation of brands; Twitter @getamobilelife; Instagram @getamobilelife; +44 07834584785