Agentic buying is redefining digital commerce by introducing a level of autonomy that didn’t previously exist in online search. Google’s latest advances in generative models and systems capable of reasoning about preferences, context, and availability have transformed the search engine into an agent capable of interpreting needs, selecting products, and completing transactions.

It no longer just displays results: it analyzes options, makes decisions, and acts. This new paradigm places Google at the center of the commercial process, taking over tasks that previously depended on the user or the ecommerce site itself.

The Quiet Shift That Changes Search Intent

For the past two years, Google has been steering commercial search toward conversational, action-oriented models. The shift is not superficial: it directly affects how products are presented, how stores are recommended, and how the user completes the purchase.

Since 2023, Google has been unifying Shopping Graph, Gemini, and Google Pay into a system that reduces steps and consolidates decisions. In the U.S., this ecosystem already makes it possible to go from a natural query, like “cozy sweater for happy hour in autumn tones”, to a ready-to-pay selection.

This evolution has direct implications for SEO: less dependence on traditional clicks, greater weight on structured inventory, and a more closed algorithmic selection. Agentic buying is not an isolated experiment; it is Google’s adaptation to a landscape where AI must solve tasks end-to-end, including the transaction.

Conversational Search with Immediate Purchase Intent

The biggest change is in the search interface. Google no longer returns a list of links but a set of products with images, availability, reviews, and integrated pricing. The AI filters the Shopping Graph inventory based on user-generated descriptions, not strict textual matches. The result is a SERP that reduces the need to browse stores: users can close the process without ever leaving Google.

This dynamic introduces a different kind of competition. It’s no longer enough to rank a product page; you now need to comply with the operational criteria of the Shopping Graph: complete structured data, updated inventory, and precise attributes. If a catalog doesn’t reflect variations like size, color, or material, the AI discards it because it cannot map it with sufficient detail. SEO becomes dependent on the quality of the feed and real-time inventory accuracy.

Shopping Graph as the Decisive Infrastructure

The Shopping Graph acts as the backbone of the process. It integrates millions of products and updates prices, stock, and images far more frequently than traditional crawling. Every element—brand, model, variants, reviews—helps determine whether a product is eligible to appear when the AI needs to propose specific items.

For SEO, this changes two things. First: the product detail page (PDP) is no longer the only optimization unit; the Merchant Center feed is now as relevant as indexed content.

Second: Google uses the Shopping Graph to reconstruct user intent. The AI interprets materials, colors, social uses, and styles. Products that fail to describe these attributes fall outside the semantic range. This makes catalog richness critical: the more attributes you provide, the more likely you are to match ambiguous or creative user queries.

Gemini as a Commerce Interface: From Prompt to Cart

In the U.S., integration with Gemini adds another layer. Queries no longer start with “product + attribute” but with needs or scenarios: “gift ideas under $40,” “clothes for a cold getaway without looking too formal,” and so on. Gemini generates a curated product selection and allows users to proceed directly to checkout.

The SEO implications are clear: if the search happens within Gemini, competition for impressions in the traditional SERP decreases. Recommendations aren’t derived from a classic ranking but from the catalog’s ability to be interpreted by the model as the optimal response. It’s not the site with the longest text that wins, but the one that describes functional product attributes most accurately and maintains a reliable inventory. Brands with incomplete feeds or mismatched prices and images are excluded from this experience.

Agentic Checkout: When Google Completes the Purchase for the User

In 2024, Google introduced the concept of agentic checkout, a system where users can follow a product, set size and budget preferences, receive price-drop alerts, and allow Google to complete the payment on compatible merchant sites using Google Pay. This flow removes the main point of friction: cart abandonment.

For merchants, this brings structural implications. Compatibility with Google Pay and simplified checkout are no longer optional enhancements: they influence the AI’s decision about which products to recommend because the goal is to reduce steps. If a store has a slow process, too many forms, or no Google Pay integration, it is less likely to be chosen for an agentic purchase. From an SEO standpoint, optimization shifts toward ecommerce technical layers traditionally considered outside the scope of organic ranking.

From Classic SEO to “Share of Agent”

Beyond clicks: competing for the agent

For years, classic SEO was measured in clicks: CTR, sessions, pageviews, etc. In agentic buying, all of this becomes irrelevant because users no longer choose between ten links—they delegate the decision to an agent that selects the best options and completes the order.

In this context, the relevant metric is no longer “share of search” but “share of agent”. This share is not won through more text or more internal links, but through:

• Reliable inventory
• Exhaustive attributes
• Google Pay compatibility
• And a frictionless checkout the agent can automate

The challenge for SEO is no longer just bringing traffic but making the business eligible—and preferable—to an automated intermediary.

What This New Environment Means for SEO

Meticulously marked product pages

Google needs to interpret the catalog unambiguously. The schema.org/Product markup must include title, main image, price, availability, brand, SKU, and variants. This is not a recommendation—it’s a requirement for products to be extracted by AI and displayed in conversational experiences. PDPs must avoid generic descriptions; if a color is not explicitly mentioned, the Shopping Graph cannot associate it with the query.

An exhaustive, always-updated Merchant Center feed

The feed becomes an extension of technical SEO. Google prioritizes products with clear titles, complete descriptions, and detailed attributes: size, color, style, material, fit, target audience. Additionally, the feed must reflect real-time availability and pricing. Mismatches between the site and the feed reduce the store’s reliability for the AI and can remove it from recommendations entirely. Feed optimization is no longer just for paid campaigns; it directly influences visibility in AI-generated purchases.

Fast checkout and payment methods compatible with Google Pay

The AI prioritizes options that minimize friction. A store with a two-step checkout, logged-in users, and simplified payment methods is more likely to be recommended. Integration with Google Pay provides clear signals of agentic compatibility: if Google can complete the process automatically, it adds that merchant to its preferred set of options. For SEO, this means that technical conversion factors influence organic visibility in agentic experiences.

Presence Across the Funnel to “Educate” the AI

Conversational queries rely on distributed signals: generic searches, informational content, brand authority, and category consistency. The more presence a store has in informative and transactional queries, the easier it is for AI to use it as a reference when a user makes an ambiguous request. Maintaining activity in broad categories and answering user questions provides context that the model uses to recommend products.

A Framework for Agentic Maturity: From Searchable to Orchestrable

Many companies think “being in Google Shopping” is enough. But when the search engine behaves as an agent, not all stores compete on the same level. We can think of four stages of agentic maturity:

• Indexable: The catalog is crawlable, pages load fast, and basic SEO is covered.
• Interpretable: Products have complete attributes (material, use, style, usage context) and a feed without price or availability inconsistencies.
• Executable: Checkout is short, Google-Pay-compatible, and designed to avoid abandonment by the user—or the agent.
• Orchestrable: The brand leverages first-party data, loyalty programs, and other agents (marketplaces, AI assistants, social platforms) to diversify acquisition and avoid relying solely on a single intermediary.

Most merchants are between levels 1 and 2. Competitive advantage in the coming years will belong to those who reach levels 3 and 4 before everyone else.

Conclusion: SEO No Longer Competes Only on the SERP

Google’s agentic buying represents a structural change: AI takes over the entire task, from interpreting intent to executing payment. For merchants, SEO now overlaps with a hybrid territory where feed quality, inventory accuracy, and checkout performance determine visibility. Brands that adapt their catalogs early will gain an advantage in a system where recommendations are not open lists, but automated selections designed to minimize friction. The time to build that infrastructure is now, before agentic experiences expand beyond the U.S. and become the default behavior for commercial search on Google.

The question is no longer whether Google will complete purchases for the user—it already does in the U.S. The real decision is this: will you allow Google’s AI to treat you as just another product on the shelf, or will you design your catalog, your systems, and your customer relationship to become the agent’s default choice?