Consumers are warming up to the idea of artificial intelligence shopping alongside them.
That’s according to new data from Algolia, which shows that 35 percent of consumers believe AI can predict fashion trends better than they can, and 34 percent of consumers trust AI to compile better outfits than they could think up themselves.
Nate Barad, the company’s vice president of product marketing, said the data the company collected indicates consumers are starting to believe AI can upgrade their experience, rather than performing mundane tasks in the background.
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“That’s a telling step, because that means that people are comfortable trusting and giving up the decision making—we’re talking about taste and creativity,” he said. “If I believe that AI can put together a better outfit for me than I can, that, to me, is a telling indicator that we’re going beyond using AI for things like efficiency.”
Algolia is upgrading its technology alongside consumers’ interest in upping their AI usage for shopping. On Monday, the company announced it would allow fashion retailers to deploy AI agents targeted at helping style consumers digitally. The agent takes into account the shopper’s history and intent, matching it with a retailer’s own inventory to suggest the best products to a shopper.
Bernadette Nixon, Algolia’s CEO, said the company’s new agentic implementation isn’t a far-off dream, but an immediate reality.
“By acting as the connective intelligence layer between customer data and front-end AI agents, Algolia empowers brands to create shopping experiences that feel as tailored and responsive as an in-store stylist,” she said. For fashion retailers looking to stay ahead, this isn’t future tech—it’s what’s possible now.”
Today, just under half—45 percent—of consumers surveyed by Algolia noted that they thought an AI-powered shopping assistant would be helpful to their experience, though only 17 percent said they wanted to see more retailers implementing that technology on their own sites.
Barad said that disconnect is likely because consumers think about chatbot giants, like OpenAI’s ChatGPT, as a source for immediate inspiration when shopping; because retailers historically haven’t given consumers the option to speak back and forth with an agent trained to handle their direct query, it’s outside of their realm of possibility.
He said adoption is likely to pick up as agentic begins to become a core piece of the customer-facing experience—and if their experience with systems like ChatGPT start to become riddled with advertisements. Today, ChatGPT’s shopping function doesn’t allow sponsored content, nor affiliate links, but Barad believes that it’s inevitably coming—and once it does, retailers with agents on their own sites will start to benefit, especially if they have already captured consumer trust.
“Once people start to realize, ‘Oh, wait a minute, I’m starting to get more advertising from a public chat than I am going [to a brand],’ that’s when they’ll start to trust the different fashion houses more,” he said.
But a chatbot experience isn’t the only AI-powered interaction with retailers consumers are interested in having. More than half of consumers said they would use AI to curate an outfit for a special occasion, and nearly two-thirds of consumers said it would be useful to have an AI system alert them that an item they wanted was back in stock.
As Algolia helps companies think about the future, it knows that incentivizing consumers to buy comes easier when a brand knows their shopper. That’s why the company has launched additional AI-powered tools, enabling merchants to do real-time personalization and tailor search rankings based on consumers’ direct preferences, rather than solely on the most commonly purchased—or popular—items, Barad said.
“With fashion, what’s popular can be very different than what’s trendy, especially given you versus me—taste,” he said. “What’s so unique to fashion is that taste is so transient, it’s so pervasive…What’s so inherent to search is popularity, and what we’ve done is to sidestep that. Popularity just does not apply in fashion; taste is too [important].”
While consumers have high interest when presented directly with a problem, they had a hard time understanding the generalized impacts of AI without a direct scenario—so when asked more broadly what they thought AI would be useful for, just three in 10 consumers said styling products.
Barad said that gap likely exists because it’s difficult for consumers to blindly imagine a use case for technology. Instead of asking a consumer whether they believe technology could be useful, asking them about a direct problem often changes their sentiment, he said.
“When we asked them about AI as an object, it wasn’t as positive,” he explained. “It was more positive when we asked them about a scenario,” Barad said, noting that has been his experience with most consumer-facing technology.
Given consumers’ rising interest in using AI to buy for themselves and for others, Barad said it would be a mistake for brands and retailers to rest on their laurels, waiting for the right time to adopt the type of technology Algolia announced Monday.
“What people don’t realize is that AI is actually trying to enhance their senses, that AI is trying to not just meet their expectations, but exceed and adjust them,” Barad said, noting that the technology has the power to change consumer expectations once available to them.
He advised that retailers collect data to underlay agentic systems and AI search upgrades but simultaneously start implementing the architecture to make agentic experiences possible.
“You’re really listening for context,” he said. “But the time is now.”
