PayPal Survey Reveals AI Shopping Agents Reshaping Commerce with Invisible Storefronts

AI agents have begun making purchases on behalf of customers, yet most merchants remain unprepared to serve them. This disconnect is the focus of PayPal’s first U.S. Agentic Commerce Pulse Survey, which collected responses from 498 decision-makers across small businesses, mid-market firms, and large enterprises.

Nearly 95% of merchants report tracking or observing traffic from AI agents, including web crawlers from systems like ChatGPT and Google Gemini. However, only about one in five have structured their product catalogs in machine-readable formats that AI agents can interpret and act on in real time. Many also lack essential infrastructure for agentic commerce, such as interoperable APIs and agent-compatible checkout systems.

This creates a market where demand is evolving faster than the systems designed to support it. “We’re seeing the interface layer move first,” says Mike Edmonds, PayPal’s VP of agentic commerce and commercial growth. He notes that while brands once competed for visibility through Google Ads and SEO, agentic commerce is shifting that pressure toward structured product catalogs and how goods appear across large language models (LLMs) and digital marketplaces.

“Where brands once competed for visibility through Google Ads and SEO, agentic commerce is shifting that pressure toward structured product catalogs and how goods appear across LLMs and digital marketplaces.”

As search becomes more intent-driven rather than keyword-driven, consumers are moving away from broad queries like “running shoes” and instead asking AI systems for highly specific, personalized recommendations. The study reveals this shift is occurring faster than merchants anticipated. Across segments, 86% to 94% of businesses expect agentic commerce to have a positive impact over the next 12 to 24 months, with many reporting it already has.

“LLMs don’t inherently privilege the largest catalog; they privilege the most structured, most trustworthy data signal,” says Srini Venkatesan, PayPal’s CTO. He emphasizes that smaller merchants with strong machine-readable data and credible signals can compete alongside larger players in agent-driven discovery. However, Venkatesan notes that many small businesses lack the resources or operational flexibility to navigate complex integrations, making broader ecosystem support essential.

Welcome to the Invisible Storefront Economy

Merchants cite access to new customers as the single biggest benefit of agentic commerce, followed by gains in personalization, repeat purchases, and sales growth. Increasingly, AI agents are handling discovery, comparison, and even checkout. This creates what PayPal executives describe as the “invisible storefront”: a system where transactions occur without a human ever visiting a merchant’s site.

For businesses still optimizing around SEO, paid acquisition, and front-end UX, this shift risks misaligned investment. Venkatesan explains that LLMs can refine messy product catalogs while applying broader contextual understanding to connect consumer needs with merchant inventory. By pairing world knowledge with structured commerce data, these systems can better interpret nuanced requests and translate them into viable purchase options.

“The agent reasons through the first layer, then queries the second.”

Despite gaps in operational readiness, trust in AI representation is higher than expected. 71% of small businesses and nearly 90% of large enterprises express confidence in AI systems accurately representing their products.