How AI Could Change Online Product Search and Discovery

The tech world is bent on making generative AI an everyday assistant to millions of customers. If it succeeds, it could have major implications for how shoppers find and buy products, including fashion and beauty.

On Monday, Apple announced that its newest phone, the iPhone 16, will incorporate generative AI models that power what it calls Apple Intelligence, a system aimed at helping users with personal tasks like writing emails, putting events in their calendar or whipping up just the right emoji for the group chat. These AI features are meant to be so integral to the phone that Apple built the device from the ground up around them. Apple will also let users access third-party tools, including ChatGPT thanks to a partnership with OpenAI.

The company is hurrying to catch up with the likes of Google, Microsoft and OpenAI as they pitch generative AI as the next big leap in technology. One area squarely in the crosshairs is online search.

A strength of the AI models underlying tools like ChatGPT is their ability to ingest large amounts of data and summarise it. The technology isn’t flawless. It doesn’t understand and retrieve information but rather uses probabilities to predict the next word in a sequence. Like any predictions, they’re not always correct. But with more data, the predictions can get better, and companies are training their models on just about the entire internet.

The result is that users can ask a question and get an answer without having to do any searching themselves. “Let Google do the searching for you,” is how Google put it when it began rolling out AI overviews for search results to all US users earlier this year.

When it comes to shopping, that may be a service consumers welcome — if it ever becomes widespread.

In a report this year, IBM found that 86 percent of consumers who hadn’t yet tried AI for shopping wanted to see how the technology could help them research products or get product information.

Similarly, Kirsten Green, a founder and partner at Forerunner Ventures, a consumer-focused venture capital firm, argued in a talk in July that consumers today feel overburdened by the amount of information available to them and are prioritising technology that can sift through it for them, driving a shift in services from what she calls “access” to “edit.”

“As a result, we now see a refreshed desire for experts and services that edit the vastness of what’s available, present the best possible options instead of more options, and do things for us instead of enabling us to do it ourselves,” Green wrote in a post. AI, in her view, offers a solution.

What a move from “access” to “edit” with AI could look like is evident when searching for products online. Right now, for example, a Google search for “best men’s gym shorts” brings up the usual list of links to reviews. A user could just make a decision based on the first link, but more likely they’d end up clicking into a few links, reading the different opinions and coming up with a conclusion — on their own — as to what’s best.

The same question plugged into ChatGPT provides a very different response. It spits out a list of shorts numbered one through 10, with bullets underneath identifying key features, the uses they’re best for and “highlights” with distinguishing characteristics.

This format doesn’t only change how shoppers get information. It can also change the information they get.

ChatGPT’s list, for example, included Vuori’s Kore Shorts. But the style wasn’t mentioned within the top four links in the Google search. On the other hand, two of those links named Ten Thousand’s Interval Shorts as the best overall. They appeared in the fifth spot in ChatGPT’s list.

ChatGPT’s list isn’t actually meant to be a ranking. The site presents its results as “some of the top-rated gym shorts.” But the numbering could be misconstrued. If that happened, the shopper would think their best option was Nike’s Flex Stride Shorts, a specific style of Nike’s Flex shorts that wasn’t specifically mentioned in any of the top four links from Google.

By digesting the information for readers and presenting answers, the AI results arguably carry even more weight than any individual link or set of reviews, which means brands whose products appear in them could benefit greatly while those that don’t might suffer. It would make AI optimisation even more crucial than search-engine optimisation, and might lead to companies looking for ways to game the results.

As researchers recently demonstrated, there are ways to do that. By adding a “strategic text sequence” to a coffee maker’s product page, they were able to “significantly increase its likelihood of being listed as the [large language model’s] top recommendation.” The New York Times recently covered other ways AI can be manipulated, too.

AI developers are aware of these issues. Google said its AI overviews use its core systems for search ranking and quality, which already have protections against these types of tactics. But just as with SEO, it could lead to an endless battle between AI companies and those looking for the best placement in the AI’s answers.

For now, however, product searches using generative AI remain an edge case. While ChatGPT quickly became an object of fascination after its public release at the end of 2022, it remains a niche product. According to Pew Research Center, as of March 2024, just 23 percent of US adults had used ChatGPT. (Though among those aged 18 to 29, the number was 43 percent.) Even those who tried it may have done so once and never again.

Some companies, including Amazon and Shopify, do have AI-powered shopping chatbots, but they might only exist in the companies’ apps.

Apple’s new phone is likely to drive usage of ChatGPT, but it’s unclear whether Apple would ever route product searches to it. Siri currently responds to those questions with a Google search.

And while Google’s AI overviews kick in for gifting-specific questions, such as “best gifts for home cooks,” the company confirmed they aren’t yet triggered by a broad range of product queries. As for whether they might be rolled out to those searches in the future, Google said it had nothing to share.