AI is reshaping how consumers shop, both on the surface and behind the scenes. From smart recommendations to voice-powered purchasing, the dream of personalized, automated commerce is accelerating. While tech companies push forward, brands are trying to navigate regulatory uncertainty and evolving consumer expectations.

In the U.S, a sweeping new AI Action Plan is creating a developer-friendly environment that is rolling back federal regulation in favor of faster innovation. Meanwhile, in Europe, lawmakers are enforcing stricter protections around how personal data can be used in AI-powered search and shopping.

Virtual try-ons, integrated checkout, and AI-powered shopping agents are rolling out first in the U.S. As AI transforms how we find and buy products, shoppers in the U.S. and EU may soon experience different versions of ecommerce. This divergence puts global retailers in a bind where they are forced to adapt quickly across regions.

This is all happening fast, but is the internet itself even ready for it?

**The Internet Wasn’t Built for AI **

Today’s web was designed for humans. It relies on visual hierarchy, “New Arrival” labels and intuitive browsing cues. Agents need structured, machine-readable data: precise product details, accurate pricing, real-time inventory and transactional capabilities.

When that structure is missing, agents move on and send shoppers to a brand with products that are clearly labeled, easy to interpret and simple to purchase. Brands without clear product structures risk losing critical traffic and sales. By 2026, it’s predicted that traditional search volume will drop 25% due to AI.

**Visibility Alone isn’t Enough **

Current AI platforms like Google’s AI Mode and ChatGPT still rely on web content that isn’t designed for agentic shopping. They pull from unstructured or outdated data, forcing agents to guess, and when the information is messy, they get it wrong or skip it entirely.

Many brands assume that making content readable is enough. But large language models don’t read web pages the way we do. They tokenize and segment content based on semantic similarity, not visual layout. That means inconsistent headings, combined topics or missing structure can cause inaccurate results or missed listings altogether.

To ensure their products are surfaced, evaluated and purchased, brands need structured APIs that facilitate two-way interactions between AI agents and their commerce system. These APIs give agents access to product data, real-time inventory, accurate pricing and the ability to complete a transaction.

Losing Data Means Losing Customer Relationships

Discovery used to start with a search. Users browsed, clicked and engaged, and in the process, brands captured valuable first-party data. As agents take over product discovery, brands risk losing direct interactions that provide insight into customer behavior. Without access to search patterns, product preferences and conversion signals, brands can’t personalize effectively, improve products or make informed strategic decisions.

But even in an agent-led environment, brands can gather meaningful signals. When APIs enable two-way exchanges, brands gain richer behavioral data than traditional website visits can offer. Those exchanges create a feedback loop essential for understanding demand, refining messaging and responding in real time.

This Shift is Already Happening

Shopify recently introduced its Catalog API, which gives agents access to structured, real-time product data. When integrated with platforms like Perplexity, this helps ensure products stay visible and easy to purchase in agent-led environments.

While Shopify’s solution allows agents to see product data, it doesn’t support two-way interaction. Brands need infrastructure that exposes real-time data, like pricing and availability, and allows agents to act on it. That includes verifying stock, updating details and completing transactions directly within the shopping experience.

Even with structured data, brands may struggle to stay visible if AI-driven search prioritizes paid results over relevance. Google is testing ad integrations in AI-driven search. Brands that can’t pay for prominence could lose visibility, not because their products fall short, but because they can’t afford the placement.

If ads dominate AI search, smaller brands may disappear from key moments of discovery, while users lose trust in the objectivity of the experience. That’s why brands can’t wait. They need to start thinking now about how they structure and communicate their data to agents.

How Brands Can Adapt

Some companies are already rebuilding for the agent-led web. They’re launching AI-native storefronts hosted on dedicated subdomains like ai.brandname.com that serve people and machines. These interfaces prioritize structured data, real-time inventory and checkout processes AI agents can navigate without delay or error.

Google I/O and Apple’s WWDC showed us what this might look like in action. As AI agents shape what we see, compare and buy, the behind-the-scenes decisions brands make will directly impact the choices in front of us. This new shopping reality is coming fast, and if brands don’t adapt, finding what we want may get harder, not easier.

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Jonathan Arena is a Co-founder of New Gen, where he’s helping brands adapt to the AI-powered internet by building the infrastructure for conversational commerce. With over 15 years of experience, he has built products used by billions of people. At Facebook, he shaped core photo, community and newsfeed features, and was a founding member of the Building 8 Innovation Lab. He went on to lead product design at Patreon and AI and ML design teams at Cruise. Arena holds a BFA from RISD and an MBA from Harvard Business School, and advises early-stage startups on the future of design and technology.