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Home » From Search To Agent-Driven Discovery
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From Search To Agent-Driven Discovery

Press RoomBy Press Room5 August 20264 Mins Read
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From Search To Agent-Driven Discovery

Adrien Menard, Co-founder & CEO at Botify, a leading agentic and AI search optimization solution for brand visibility.

​For nearly two decades, digital commerce followed a predictable pattern. Brands optimized sites, ranked higher, drove traffic and converted visitors into buyers. This model assumed there was a human on the other side of the screen searching for products, clicking through results, reading product pages, weighing options and eventually making a purchase. But this assumption no longer holds.

We recently published an analysis of more than 7 billion OpenAI log files tracking AI bot activity across enterprise retail sites and found that OpenAI’s web crawler tripled its activity in 2025. This means your site is already being audited, with retail and e-commerce seeing a 194% increase in activity from the agents driving AI search results. If your product pages aren’t ready for AI access now, that incomplete snapshot may be what ChatGPT draws on for several months.

As agentic commerce progresses, we move closer to the reality where each shopper has a personal AI agent authorized to make purchases on their behalf based on purchase history, preferences and budget. But to be recommended to a shopper, products need to be accessible to agents. If AI readiness isn’t prioritized, brands risk being left behind.

Why Most Brands Aren’t Ready For Agentic Commerce

Most existing product feeds and catalogs today were built for Google Shopping or paid media channels. They cover the basics, like title, price, image and description, but they’re thin on the contextual information that AI agents rely on to make recommendations, like customer reviews, Q&As and detailed specifications. Without that depth, AI systems don’t have the confidence or the data to surface your products.

There’s also a critical content problem that doesn’t get enough attention at the leadership level. AI bots can’t process JavaScript-heavy pages the way a browser does. If your product pages rely on client-side rendering, an agent may see an incomplete version of what you offer. You could have the best product in your category and still not show up because your page wasn’t ready to serve an AI agent.

And when product data is inaccurate across channels, the damage compounds. Where a human shopper might overlook small discrepancies, an agent evaluating hundreds of sources will deprioritize yours.

The Protocols That Will Define The Next Era

The infrastructure for agentic commerce is being built in real time, with OpenAI, Google and Microsoft striving to develop the protocol that will be adopted by the masses.

OpenAI’s Agentic Commerce Protocol (ACP) defines how AI agents interact with commerce platforms—the structured formats that product data must follow for agents to reliably discover, evaluate and recommend. Google’s Universal Commerce Protocol (UCP), launched in January 2026 with partners including Shopify, Visa and Walmart, creates a standardized framework for AI-driven purchases, covering authorization, payment and fulfillment. This led the way for Google’s new intelligent shopping cart, Universal Cart, which enables easy purchases across merchants and services. WebMCP, co-developed with Microsoft engineers and currently in early preview in Chrome, addresses a different piece: While structured data like Schema.org describes what things are on your site, WebMCP describes what an agent can do there. In practice, WebMCP handles the interaction and UCP handles the transaction.

Brands that start building for these protocols now will have a head start over the competition, both in technical readiness and in the institutional knowledge that comes from testing and learning early.

Push, Pull And Where Strategy Lives

There are two main levers for getting your product data into AI systems: making it easy for AI to pull what they need from your website and pushing information directly. Most brands only do one well.

“Pull” is the familiar model where AI systems crawl your site, find product pages and content and incorporate that information into their knowledge base. Getting the “pull” right means your site is technically accessible to bots, your pages render completely and your content has enough depth to be useful.

“Push” is proactive, skipping the need for crawling. Instead, you can send structured product data directly to AI platforms so they have your current catalog in the formats they need, without waiting for an agent to extract it from your site on a delay.

The brands that show up consistently in agentic commerce will do both.

From E-Commerce To Agentic Commerce

AI shopping innovation, protocol adoption and consumer behavior are all moving in sync, and the brands investing now are already building feedback loops. They’re learning what drives AI visibility, refining their data and strategy and establishing themselves as reliable sources.

Start treating your catalog, product pages and site architecture as the infrastructure that AI agents need.

Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?

Adrien Menard
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