If you have spent any time reading about AI lately, you have probably come across the term “agentic commerce.” I have spoken with more than 20 merchants in the past three months, most in traditional categories such as fashion, beauty, and home living. Their reactions were almost identical: “It sounds important, but I have no idea what it actually means.”
You are not alone. The term is used often, sometimes in ways that make it sound more complicated than it is. So let’s cut through the noise and explain what agentic commerce is, why it matters for your business, and what to do about it.
The Simple Definition
Agentic commerce is what happens when AI agents—not humans—do the shopping.
Instead of a person browsing your website, comparing prices, and clicking “buy,” an AI agent does that work on the customer’s behalf. For example, a customer might tell an AI assistant, “Find me a solid pair of running shoes under $100 with good cushioning.” The assistant evaluates options, selects one, and either recommends it to the user or completes the transaction directly.
For merchants, this is a fundamental shift. For the past 20 years, you have optimised for people landing on your website or mobile app. Now you also need to consider whether an AI agent can find you, understand what you sell, and choose you over a competitor.
How We Got Here
Commerce started in physical stores, moved to websites, then to mobile apps, and later to messaging channels such as WhatsApp and Instagram. Each shift moved the merchant closer to where customers already were. Agentic commerce is the next step, but customers are not simply in a new place: they are increasingly represented by AI agents.
Think about how you book a flight today. You may still open a travel website, compare prices, and make the final choice. Now imagine telling your AI assistant: “Book me a flight to Tokyo next Friday, under $500, with no stopovers.” The assistant handles the rest. That is agentic commerce in a nutshell.
It is already emerging in categories such as travel, food delivery, and ecommerce. Over the next few years, it may expand into more categories where a purchase decision can be reduced to clear criteria.
Why This Matters for Merchants, Including Small Ones
Discovery Is Changing
When customers ask AI assistants for recommendations, the assistant may draw on structured data, verified sources, and the information available to it. If your business is not prepared for how AI agents find and compare options, you may be absent from an important discovery channel.
Decision Criteria Are Getting Stricter
A human shopper may buy from you because they like your brand story or find your images appealing. An AI agent needs facts it can compare: price, features, availability, reviews, return policies, and more. Merchants that present those facts clearly are easier for an agent to evaluate.
The Middleman Is Changing
Historically, the middleman was Google, Amazon, or Facebook. In agentic commerce, an AI assistant can become an additional layer between customers and merchant offers, alongside networks that connect AI agents to those offers.
The New Infrastructure Layer
Agentic commerce does not happen magically inside a chatbot. There is a technical layer behind it.
When an AI agent needs to recommend a product, it needs a structured way to find merchant offers, verify them, track whether the user clicked or bought, and settle payments or commissions afterwards. An AI assistant does not necessarily handle those functions on its own; it needs supporting infrastructure.
This is where services such as the Agent Offer Network (AON) come in. AON is a structured offer layer that connects AI apps and agents to merchant offers, supporting discovery, attribution, and settlement behind the scenes. You do not need to understand every technical detail as a merchant, but this middle layer helps explain how AI agents can surface real, purchasable products.
The takeaway is not that every merchant needs to integrate with a specific platform immediately. It is that agentic commerce is supported by real infrastructure and is becoming easier to operate at scale.
What Merchants Should Actually Do
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Make your product data machine-readable.
Clean up your product feed, add appropriate schema markup, and make sure prices, descriptions, availability, and shipping information are structured, accurate, and current. If an agent has to guess whether an item is in stock, it may skip the offer. -
Keep information consistent across channels.
If your website shows one price, your Google Shopping feed shows another, and a third-party marketplace listing shows something different, you have a problem. AI agents may cross-reference sources, and inconsistent information can make an offer harder to trust. -
Invest in trust signals.
Reviews, ratings, verified certifications, and return policies give AI agents facts they can use to assess whether a business is credible. They may be unglamorous, but they are important. -
Optimise for AI discovery, not only Google.
Google SEO techniques are still useful, but they are no longer the complete picture. Consider how AI assistants such as ChatGPT and Claude can find and describe your business. Some merchants also evaluate PingPlus for performance-based AI-assisted discovery, paying when an AI-driven recommendation results in a real customer. -
Plan for direct agent integrations.
Over time, consider how AI agents could transact with your store through APIs, structured product feeds, and agent-friendly protocols. You do not need to build this today, but it is worth understanding where commerce is heading.
The Bottom Line
Agentic commerce is not just a buzzword. It is the next evolution of how customers find and buy products, and it is already reshaping which merchants are easier to discover.
It is real, it is growing, and it is easier to start preparing now than to catch up later.
FAQ
What happens when an AI agent shops on a customer’s behalf?
An AI agent can handle the discovery and comparison work that a customer would normally do: finding options, checking criteria, and narrowing the choices. Depending on the experience and available integrations, it may recommend a product to the customer or complete the transaction directly. Either way, the agent becomes an early evaluator of the merchant’s offer.
If Google, Amazon, and social media still bring me customers, why should I care about agentic commerce?
Those channels can remain important, but an AI assistant may become an additional layer between the customer and the merchant. It can evaluate options and present recommendations before a customer reaches a marketplace or merchant website. That creates a separate discovery path shaped by how well the assistant can understand and compare your offer.
What should I check first to see whether an AI agent can evaluate my products?
Check whether your product pages clearly state the facts a customer would use to compare options: price, features, availability, shipping, and return terms. The information should be accurate, current, and easy to parse. If an agent has to guess whether a product is in stock or meets a customer’s requirements, it may favour a clearer alternative.
What can I do now without building new AI integrations?
Start with the systems you already control. Keep product data consistent across your website, product feed, and marketplace listings; make prices and policies visible; and maintain genuine reviews and other trust signals. These improvements make your existing offer easier to evaluate today and create a stronger foundation for future agent integrations. If you also want to test performance-based AI-assisted discovery, PingPlus is a separate option to evaluate while you continue building that foundation.
Should I consider joining an Agent Offer Network (AON) now?
It can be worth evaluating now, especially if your products already have reliable prices, availability, policies, and conversion tracking. An Agent Offer Network can help connect merchant offers with AI apps and agents for discovery, attribution, and settlement. Before joining, evaluate whether the network supports your category, offer type, and commercial terms.
