The fashion-forward future of artificial intelligence

How new technology at Amazon and Botika is revolutionizing the way we shop

Richard Avedon. Dovima with Elephants, evening dress by Dior, Cirque d'Hiver, Paris, August 1955. The Richard Avedon Foundation.

Shopping for clothes used to be a uniquely tactile experience—wandering through malls or strolling down trendy streets lined with indie boutiques and hipster cafés.

It was a Saturday afternoon ritual, filled with the thrill of discovery, chatting with salespeople, and finding that perfect fit. There was a certain satisfaction in knowing you’d sourced your $200 pair of selvedge jeans from the coolest shop in an oversized paper bag that boasted your brand allegiance, and pairing the moment with a frothy mocha latte from the café next door.

Maybe the barista was wearing the same jeans—his cuffs flipped up, already showing that perfectly worn-in patina you were striving for.

The pandemic pulled us off the streets and onto our screens, fuelling a newfound hunger for online shopping—though, at the time, it was mostly for comfy sweatpants and designer face masks. Fast-forward five years, and as return-to-office policies become the norm, you’d expect a resurgence of leisurely shopping trips. But our habits have changed.

Instead of strolling through boutiques, we’re turning to online shopping more than ever—this time, with a sharper focus on finding pieces that fit well and reflect our individual styles.

AI-powered shopping experiences

Amazon was once the go-to for basics like cotton underwear and plain white T-shirts, but its Clothing, Shoes & Jewelry category has experienced significant growth, especially in luxury fashion. It recently rolled out AI-powered tools designed to enhance both the shopping experience for consumers and for brands analytics.

Machine learning now analyzes past purchases, returns, and reviews, cross-referencing them with similar shoppers to provide personalized product and sizing recommendations. The algorithm even adapts over time—if you bought children's clothes in January, it will suggest larger sizes in later months as your child grows.

On the seller side, Amazon’s Fit Insights tool measures shopping performance, tracking return rates, reviews, and other data to help brands refine their offerings and pricing. While Amazon has the financial and technological muscle to lead in AI-driven fashion retail, other retailers are quickly following suit.

A report by McKinsey & Company suggested AI could add $275 billion profit to the fashion and luxury industry over the next five years. Online shopping generates high return rates, which cut into profits, and brands are betting that better recommendations will reduce returns and improve customer retention.

No more models or photographers

Another AI-driven shift in retail is being led by Botika, a platform that generates AI-powered models and product photography, eliminating the need for human models and photographers on either side of the lens. Already adopted by some Shopify merchants, Botika streamlines content creation—brands simply upload a photo of their garment, select an AI-generated model and background, and receive a set of dynamic images featuring various poses.

The result is a seamless, cost-effective way to produce polished marketing visuals without the traditional time and expense of photoshoots.

But this efficiency comes at a cost. The organic collaboration between photographers, stylists, and models—once central to fashion imagery—is further diminished. While e-commerce photography has long prioritized efficiency over artistry, Botika takes it a step further, absorbing the spontaneous energy, style, and unique brand identity that comes from real-world and in-studio collaboration. Anyone who’s been on a fashion shoot knows that the magic often happens in the unplanned moments, where creativity sparks in ways no algorithm can fully replicate.

My grain of thought

Lately, I’ve come across more and more first-person accounts of fashion seekers turning to ChatGPT as an AI-powered personal shopper, hoping it could help them source the perfect look for their age, profession, or an upcoming event. But most didn’t walk away satisfied—ageism and other biases often derailed the experience, making it more frustrating than helpful. Part of the issue? ChatGPT isn’t designed to be a personal stylist… yet.

As open-source AI becomes more democratized and chatbots evolve into highly specialized assistants, I predict we’ll soon see personalized AI shopping agents tailored to individual preferences. Imagine an avatar that matches your exact size, shape, and appearance, seamlessly navigating a retail metaverse, modeling outfits in real time. These AI-powered shoppers could even project our digital selves into specific settings—a creative office, a rooftop cocktail party, or a weekend getaway—helping us visualize how a piece of clothing would look in context before we buy it.

AI is reshaping how we shop, from hyper-personalized recommendations to virtual models and metaverse styling assistants. But as we trade spontaneity for precision and efficiency for convenience, what do we lose? The thrill of discovery, the tactile joy of trying something on, the creative spark of a real photoshoot—these are hard to replicate, even for the smartest algorithm. As AI evolves, the real challenge isn’t just perfecting virtual try-ons but keeping fashion personal, expressive, and human.