AI Agents Are The New Personal Shoppers In Online Fashion

Retailers are betting on AI agents to cut returns, boost conversions, and make fashion shopping feel truly personal.

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Earlier this year, the global fashion e-commerce market crossed the $1 trillion threshold for the first time, according to Statista. But while that growth is commendable, it also comes with challenges, like higher returns, inconsistent sizing and frustrated shoppers overwhelmed by endless scrolls. Despite powerful recommendation engines and filters, the experience still feels impersonal — like a one-size-fits-all offering in a world demanding nuance.

That’s where a new class of AI “fashion agents” is emerging. Rather than just recommending items, these generative AI tools aim to act more like stylists: learning preferences, anticipating needs, and tailoring suggestions to the way people actually shop. One startup racing for leadership in that space is California-based Gensmo, whose founders say they’re building an entirely new interface between fashion and consumers.

In late June, Gensmo announced that it had raised more than $60 million in angel funding to accelerate development of its AI-powered platform. With a background that includes roles at Google, Newegg and multiple successful exits to Nasdaq-listed companies, co-founders Ning Hu and Gene Deng believe the future of online retail lies in intelligent, adaptive agents, not just static search bars.

The Rise Of Adaptive Agents

When most shoppers search for fashion online, they rely on structured filters: Size, color, occasion and price. But real-world style decisions rarely follow that logic. “People don’t shop by spreadsheets,” said Hu. “They shop based on mood, fit, inspiration and how they want to feel in a particular moment.”

Gensmo’s platform takes that complexity seriously. Instead of treating a shopper’s query as a one-time request, it uses a multimodal AI model to understand their body shape, lifestyle, taste, and past behavior — then offers personalized styling solutions. Think of it less like a search engine and more like an always-on style assistant.

“We’re not here to build another widget,” she explained. “We want to create a solution engine that truly understands you — how you live, what you care about and what actually looks good on you.”

That kind of personal context is becoming essential today. According to McKinsey’s 2024 State of Fashion report, personalization and convenience are now two of the top drivers of e-commerce satisfaction globally. Nearly 71% of consumers said they are more likely to shop with brands that offer tailored experiences — a trend that’s only accelerating with the integration of generative AI.

When Shopping Becomes Personal

At the heart of Gensmo’s system, whose user base is predominantly Gen Z, is its virtual fashion agent, which goes beyond basic outfit suggestions. It can simulate try-ons, adjust recommendations based on your calendar (like a sudden beach trip) and help you build a wardrobe over time. Users can also explore features like AI avatars, try-on videos, outfit collages and photo-based interactions.

“Gensmo was built to feel less like a tool and more like a relationship,” Hu told me. “The more you engage, the more accurate, useful and intuitive it becomes.”

The company is careful to frame this as augmentation and not replacement, especially as concerns about AI-induced job displacement continue to grow. While some fear that AI in retail may reduce human creativity or eliminate stylist jobs, Deng said the goal is to empower both shoppers and fashion professionals.

“There’s always going to be room for human taste, for designers, for creativity,” he noted. “What we’re doing is helping close the gap between inspiration and action — so people can actually find and buy the looks they love.”

As Sheena Butler-Young notes in her report for Business of Fashion, AI is increasingly moving beyond inventory and copywriting to creative functions traditionally reserved for humans — such as photography, styling and PR strategy. The report emphasized that designers can maintain their edge by integrating AI into their workflows while doubling down on distinctly human strengths like emotional intelligence, cultural fluency, storytelling and authenticity.

Gensmo’s cofounders agree and believe the first place to start is with the shopping experience itself.

Trust Over Traction

As with all AI products, especially those using sensitive personal data like body shape or sizing, privacy and transparency are critical. Gensmo’s cofounders are candid about the importance of trust in the fashion space, especially when you’re recommending what someone should wear to a wedding, job interview, or date night. That’s why many platforms, including Gensmo, are framing privacy as a design principle — giving users control over what is stored, learned, or shared.

As Deng put it, “AI doesn’t just need to be smart. It needs to be respectful. The bar for trust is high when you’re helping someone choose how to show up in the world.”

Interestingly, that trust is also financial. Return rates in fashion e-commerce have long hovered around 30% or higher, and many retailers are still losing money on reverse logistics. But new tools may offer relief. Retailers that deploy virtual try-on technologies typically see about a 30% increase in conversion rates and a 20-30% reduction in return rates, according to a research summary on Focal.

That’s a compelling pitch not just for consumers, but for fashion brands looking to retain customers and reduce costs in a tightening retail environment.

The Next Evolution In Consumer AI

Gensmo isn’t the only company rethinking how we shop. Other startups, like Vue.ai and Stylitics, are also racing for leadership in the space, offering AI-powered styling recommendations. But Gensmo’s cofounders said only a few startups are attempting the full end-to-end experience — from body-type understanding to vacation wardrobe planning — that Gensmo is pursuing.

Still, the space is evolving quickly. According to a Capgemini report, more than half (56%) of retailers increased their investments in generative AI over the past year, and 18% have already implemented AI agents or multi-agent systems in production operations. And as these technologies become more embedded, consumer expectations regarding personalization and AI-enhanced shopping experiences continue to rise, with Saks Global finding that two-thirds of luxury shoppers now use AI features when browsing online, and 94% say they’re open to more personalized experiences.

“There’s no going back,” said Hu. “People now expect the same personalization from a fashion site as they do from Spotify or Netflix. Generic results are no longer sufficient.” Deng added that Gensmo believes “the next generation of fashion platforms won’t just show you clothes; instead, they’ll understand you well enough to show you what flatters before you even know how to ask for it.”

In what might turn out to be one of AI’s most consumer-facing use cases, that expectation might represent the largest shift of all. What began as recommendation widgets is becoming a deeper relationship between consumer and platform, where AI doesn’t just show what’s available but what actually fits, flatters and feels right.

Whether those promises are fulfilled will depend on both technical implementation and whether or not customers feel the machines dressing them genuinely understand and value them.