Consumers have quickly adapted to generative AI tools when shopping online, according to Capgemini Research Institute’s 2025 consumer trends report.
Seven in 10 respondents are keen to have it integrated into their purchasing experiences and nearly half — 46% — are enthusiastic about the impact of generative AI on their online shopping, the global survey of 12,000 adult consumers found.
As generative AI changes consumer shopping behavior, brands will need to quickly adapt to facilitate conversational search and create tools that quickly and seamlessly guide customers to products and services, experts said. With first-mover advantage going to forward-looking brands, now is the time to get started.
With customers favoring the convenience and personalization of generative AI tools, brands have an opportunity to improve customer interactions by adapting and optimizing experiences based on behavior patterns, according to Gabriel Bridger, global head of experience and strategy at Rightpoint.
“The best part is that [generative AI tools] can be personalized and continuously iterated without disrupting the entire experience,” Bridger said.
The major benefits of AI-powered shopping tools are saving time, easier navigation and better product recommendations, Bloomreach has found.
Eyeing the opportunity to improve product search across its mammoth catalogue, Home Depot recently introduced its Magic Apron tool. It’s an AI-powered digital store assistant that streamlines and simplifies the product search while continuing to offer standard online navigation.
Digital design experts such as Bridger believe tools like Magic Apron are an example of using the technology to address genuine pain point that can translate into better customer experience.
“It offers another smart way to navigate the dense product details and specifications in a simple chat-based interface,” Bridger said.
Where should brands start?
To get started, brands can focus on adding conversational tools to existing structured navigation to improve the online experience and respond to changing customer behavior.
“Brands should start by layering AI-powered enhancements into existing systems, rather than replacing them outright,” Bridger said. “It sets the stage for brands to test and learn their way into the future.”
By layering the technology, businesses can continue to cater to consumers who favor menus and structured navigation while offering interactive tools as well.
Bank of America’s virtual assistant Erica is a case in point. The bank combines structured menu options with AI-driven conversations to provide financial insights and transaction assistance.
To maximize engagement and customer benefit, these tools must align with the customer’s preferences and their expectations of the brand, Bridger said.
For example, L’Oréal’s AI assistant Beauty Genius blends traditional navigation with conversational AI. The virtual beauty assistant offers personalized product recommendations and beauty routine suggestions.
“It depends on who your customer is, what they need, and how the experience is designed,” he said.
The risk vs. reward of generative AI
Ignoring AI could translate into lower engagement and customer retention. Now is the time for brands to take their first steps by experimenting with generative AI, even though they may be unsure of the outcome, experts told CX Dive.
“There's a lot of CapEx spend going into AI at the moment with not a lot of guarantees, so it's very high risk,” said Tadhg McCarthy, founder and chief design officer at Elsewhen.
Despite this, he believes that the biggest risk is getting left behind.
“Without these experiments, they could miss this fundamental shift in how customers want to engage with their brand and having their systems prepared for that,” he said.
There’s usually significant work so that internal data systems are compatible with the technology, according to McCarthy. In particular, siloed data and lack of interconnected systems are the most common challenges.
“The path forward is creating the digital piping and finding ways for AI agents to connect to your systems,” McCarthy said.
This restructuring work will position brands to embrace AI agents that can offer recommendations, track orders and make simple transactions on behalf of consumers.
Align metrics and tread carefully with data to deliver CX gains
To prove their worth, generative AI tools must drive measurable improvements in customer engagement. Customer adoption and engagement rates are the most obvious way to track their effectiveness, according to Bridger.
“Use CSAT, NPS and sentiment analysis to gauge user satisfaction and even how it ultimately affects brand affinity,” Bridger said.
However, Bridger warns customer expectations rise quickly and limitations in the technology can turn into disappointing experiences that show up in brand metrics.
“AI that doesn’t remember past interactions or misunderstands simple concepts can turn customers off and also reflect poorly on the brand,” he said.
To build trust and encourage adoption, brands must also be careful about the amount of data they’re capturing and how and where it’s used. Too much personalization can feel invasive and lead to a lack of trust if not handled properly, according to McCarthy.
Education can help customers understand what personal information they’re handing over when using AI systems, but brands should only capture what’s necessary. Failing to tread responsibly, could backfire.
“It will come back to bite these companies in the end if they don't figure out how to use customer data without abusing their position,” said McCarthy.
