How AI is disrupting the modern consumer shopping journey

The modern consumer shopping journey is being transformed by the rapid rise of artificial intelligence (AI). AI has made shopping more conversational and personalized as people shift from traditional search engines and toward AI-driven platforms.

Customers are turning to generative AI tools for inspiration, engagement, and active decision-making support, including summarizing various reviews, comparing prices, and then generating shopping lists in real time. In fact, a recent study revealed that half of U.S. consumers¹ say they use AI assistants during shopping, emphasizing a brisk pace of transformation for the retail experience.

During KeyBanc Capital Markets’ 2026 Emerging Technology Summit in March, Ava Jodlowski, AVP, Mosaic Product Manager at KBCM, convened a panel of thought leaders to discuss this topic. Chris Moulton, Search Lead at Ben-Her Marketing; Jonathan Snow, CIO and Co-Founder of Avenue Z; and Elaine Kwon, Co-Founder and Managing Partner at Kwontified, discussed just how quickly the pace of this transformation is happening. They talked about its impact across brands, retailers, and various e-commerce platforms and reviewed why the evolution of search and discovery is reshaping where and how the path to purchase begins.

From search engines to AI interfaces

For decades, traditional search engines served as the primary gateway to online shopping, where consumers entered short, keyword-based queries. Shoppers would then scan a list of links and navigate across multiple websites before coming to a decision.

That model has now changed. “We’re moving from a world of keyword stuffing and density to building trust and relationships between entities,” explained panelist Elaine Kwon. “It is a very different game.”

Kwon said that AI-powered platforms are changing how consumers initiate their shopping journeys. Users are asking contextual questions, many of which are highly specific or personalized. That shift in how the shopping journey starts also alters how products are being discovered, she said.

AI synthesizes the information, evaluates options, and then delivers curated answers for shoppers. Many times, the consumer doesn’t even leave the interface to browse multiple sites. Instead, they start and progress within a single AI interaction.

Sixty-one percent of shoppers use AI for price comparison,² with nearly one in five building AI-driven lists or trackers ahead of big sales events like Cyber Monday. According to panelists, product delivery is now bifurcated, with a large portion still starting on traditional marketplaces, while AI-driven entry points are growing quickly. Because of that, brands are competing for visibility across search engines and retail platforms as well as within AI-generated responses.

Chris Moulton noted that Google and Microsoft Bing, for example, are actively experimenting with where to place AI overviews on the search results page.³ Sometimes they place them above paid ads, and other times they are embedded mid-page. That placement could vary based on user behavior and comfort with the feature, with less adaptive users potentially seeing it positioned lower or not at all.

Google, in particular, he added, faces a dilemma because its revenue model depends heavily on paid search ads. If AI overviews push those ads too far down the page, it could erode revenue or undercut its core business.

AEO is changing the rules for visibility and engagement

Not only is AI changing search behavior, but it is also changing the rules of visibility. Traditional SEO centers on keywords and backlinks, but Answer Engine Optimization (AEO) is quickly entering the picture. In the AEO environment, structured, credible, and context-rich information is prioritized over rewarding for density, panelists explained.

AEO favors well-organized product data, third-party validation, and authoritative mentions as well as consistency across digital touchpoints.⁴ For brands, this means it is important to make content machine-readable and not just human-readable. AI systems rely on structured data to interpret, compare, and recommend products, so having that is essential. Brands that don’t have it, even if they are high-quality products, could be invisible in AI-generated outputs.

Since AI models draw from a wide range of sources, it is also important to be featured in third-party content, which can have a major influence on whether a product is brought up in AI responses.

The new path to purchase

Traditionally, the path to purchase followed a funnel, which included awareness, then consideration, and then conversion. Each of those stages included distinct touchpoints and opportunities for influence. Now, AI is collapsing that funnel and creating a new path to purchase.

For example, panelists noted that when a consumer asks an AI assistant for a recommendation, they are often signaling both awareness and intent simultaneously.

“Customers are already asking AI platforms, ‘I want a new water bottle for my office that will keep my coffee hot for 12 hours and fits in my car cup holder,’” Kwon said. “The AI’s response might then include a list of products, with summaries, measurements, comparisons, and direct purchase links.”

This compression of steps (where AI essentially performs the consideration phase for the user) means that there are fewer touchpoints to brands before deciding. The other difficult part for brands is that they have less control because the messaging is mediated through AI interpretations, not through direct brand communication.

Measuring performance or success can also be more difficult since AI-driven interactions aren’t compatible with usual referral data or click tracking, panelists explained.

Considerations when AI is your shopper

If AI-powered search is changing the discovery piece, agentic commerce will change the entire transaction process, explained Jonathan Snow, whose company is a full-service performance marketing agency specializing in Shopify brands.

Agentic commerce is when AI systems recommend products as well as execute purchases on behalf of the consumer and typically have minimal or no human intervention. According to Snow, it will be a big shift in consumer behavior in the future, but there are still trust issues consumers face, so the need for incentives to build consumer confidence is key.

Other panelists also pointed out the potential role of “supervisor agents,” which are secondary layers of AI that can review and validate transactions before they are complete.

Data is also a major deciding factor when AI is your shopper, because for an AI agent to make a purchase, it has to have access to accurate and up-to-date product information. For this reason, brands have to make sure their data infrastructure can support this by including things like specifications, pricing, availability, and fulfillment details.

How to prepare for an AI-driven shopping journey

As shopping habits continue to change, brands’ approach to marketing must also change to stay visible and competitive. Panelists say that brand teams will be more tech-enabled with product information that is easy for machines to understand and access.

New tools are also emerging to help brands track how they appear in AI-generated outputs, while middleware solutions are being developed to ensure brand data translates effectively across platforms, explains Snow.

Snow also noted that agencies that understand the growing possibilities of what can be done in the advertising world and that stay ahead of constant platform updates are the ones that will win bigger and better clients.

Just as important, panelists pointed to the ability to communicate with engineers. Brands aren’t hiring large numbers of engineers to build tools from scratch. Instead, they’re using tools that have been built by engineering teams. The important part is to have teams that know how to effectively communicate with those engineers and that have a technical understanding of how the tools work.

In the end, the modern consumer shopping journey is an intelligent, adaptive system shaped by AI at every stage. Success for brands will depend on being visible within AI systems and staying agile as the technology evolves.

About the Emerging Technology Summit and Mosaic

The 21st Emerging Technology Summit in San Francisco brought together technology leaders from public and private companies, alongside industry executives and institutional, VC, and PE investors. Participants engaged in high-impact discussions and gained valuable perspectives on emerging trends shaping the market. Mosaic provides insight and front-line perspective into the topics and themes impacting our clients’ portfolios and research agendas, working to identify the next wave of innovation ahead of industry-wide disruption. Together, Mosaic and KeyBanc Capital Markets provide an unparalleled competitive advantage in an ever-changing, dynamic market.

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