Is Your Brand Ready for Agentic Commerce?

Your company’s products or services may rank well on Google and Bing. Your social media ads may still be driving traffic to your website, and you may be getting sales from that traffic. But what happens when the customer never visits your website?

Imagine someone asks an AI like ChatGPT, Claude, Grok, or Perplexity to research a product, compare the best options, choose one that meets a specific set of user requirements, and place the order, all without ever leaving the AI experience.

Welcome to Agentic Commerce.

Before AI, using traditional search engines like Google, Bing, or DuckDuckGo, a common search phrase might have been:

“brown leather laptop bag that fits a 13-inch laptop”

From there, you would visit websites, look at product specifications, read reviews, and make a purchase. Or, if you were not quite certain, maybe you would add one to a shopping cart, take a screenshot, or keep searching for the perfect laptop bag.

AI has changed search in a way that is forcing businesses to rethink how they present information online.  Now, a conversation with an AI like ChatGPT or Claude might begin with: “I need a new laptop bag.”

Depending on how much prior information you have shared with the AI, it may already know that you like natural materials and quality products. It might know that you prefer brown leather over black. If it helped you choose your laptop, it might even know the exact model you own and its dimensions.

If the AI is connected to your calendar, or if you have had previous conversations about work or travel, it might also know that you have a major presentation in two weeks and will be flying. All of those known variables become data points an AI agent can use to search across multiple sellers, compare product specifications, evaluate price and availability, check shipping and return policies, and identify the products that best match your needs.

As commerce integrations continue to develop, the agent may also be able to add the selected bag to a cart and help complete the purchase. That means that if you are in the business of selling laptop bags, the information you provide about each product needs to be detailed enough for AI to determine whether your product belongs in the conversation when it is a match for that specific person’s needs and preferences.

The same idea applies to services. Someone might ask: “Find me a highly rated roofer near me who works on metal roofs, offers financing, and can inspect the roof next week.”

Instead of simply returning a list of search results, an AI agent may evaluate local roofing companies against those requirements, compare reviews and qualifications, identify which businesses serve the area, and potentially move directly into scheduling an inspection.

The AI is no longer just helping someone search. It is becoming part of the buying process.

What Is ACO, or Agentic Commerce Optimization?

This is where ACO, or Agentic Commerce Optimization, comes into play. ACO is the first of the 4 C’s of External AI Readiness, a framework created by strategy consultant, Stacy Nelson, to help businesses and marketing professionals evaluate how prepared they are for AI search, product discovery, and agentic commerce, regardless of which tools, platforms, or technical protocols they ultimately decide to use.

The 4 C’s are:

1. Compatibility (ACO): Does the product or service fit what the customer is asking for, and can the AI take the next step?
2. Clarity (AEO): Can AI clearly understand what you offer and the details it needs to evaluate it?
3. Credibility (GEO): Is there enough reliable evidence for AI to trust your business and its claims?
4. Consistency (BCO): Does the information about your business agree everywhere AI encounters it?

Agentic commerce puts particular pressure on Compatibility because matching the customer to the right product is only part of the job. The AI may also need access to current pricing, inventory, shipping, delivery information, reservations, appointment availability, or checkout systems before it can act. 

Brands Are Still Figuring Out What “Ready” Means

The infrastructure for agentic commerce is still developing, and brands, ecommerce platforms, payment companies, and AI providers are all working out how these systems will communicate.

But one thing is already becoming clear: Having a product online does not automatically mean an AI agent can use it.

At Stripe Sessions 2026, Klarna’s Head of Agentic Commerce Payments, Darren Moore, described a major global activewear brand with roughly 160,000 products live and in stock. Only about 10,000 of those products were discoverable by AI agents. The products existed. Customers could purchase them. But gaps in the underlying product data, including missing product identifiers such as GTINs, made much of the catalog difficult for AI systems to reliably identify and reconcile.

That is a significant distinction. A product can rank in Google, appear on a retailer’s website, and be perfectly purchasable by a human while still being difficult for an AI agent to confidently identify, compare, recommend, or purchase.

That is why agentic commerce readiness is bigger than adding an AI-friendly checkout option. It starts with the information surrounding the product or service itself. And this is where the 4 C’s become especially useful.

A Roofer Preparing for Agentic Commerce

Imagine a roofing company whose website ranks well locally and prominently says:

“Quality roofing services since 1987.”

That works as marketing copy, but it does not give an AI agent enough information to determine whether the company is right for a specific customer.

If the customer asks for a highly rated roofer who works on metal roofs, offers financing, serves their neighborhood, and can inspect the roof next week, can AI determine that this company is a match?

That requires Compatibility and Clarity.

The company needs to clearly communicate its service area and the types of customers and properties it serves; the roofing systems, materials, projects, and related services it handles; its licensing, insurance, certifications, experience, and warranties; inspection, estimate, emergency-service, and scheduling availability; pricing factors, payment and financing options, and insurance-claim support; permit and code responsibilities; what customers should expect before, during, and after a project; any important limitations or exclusions; and how to request service or take the next step.

Credibility matters because the AI also needs enough evidence to determine whether claims about experience, licensing, certifications, and reputation can be trusted.

Consistency matters because the company’s website, Google Business Profile, directories, reviews, and other sources should all tell the same story.

Then comes the agentic part. If the roofer is a match, can the AI actually request an inspection or schedule an appointment? A roofing company with clear service information and connected scheduling will be in a much stronger position than one whose details are scattered across webpages, old directories, and outdated profiles.

A Restaurant Preparing for Agentic Commerce

Now imagine someone asks:

“Find a restaurant near me with gluten-free options, outdoor seating, good reviews, and a table for four at 7:00 tonight.”

A restaurant may rank well on Google and have a large social following.

But that does not automatically mean an AI agent can confidently recommend it.

The AI needs to determine the restaurant’s current hours and operating status; its cuisine, menu, dietary accommodations, and how clearly those options are identified; its location, atmosphere, seating options, and other relevant amenities; what diners and credible third-party sources say about the experience; real-time table availability for the requested date, time, and party size; and whether it can complete the reservation through an available booking system.

Again, all four C’s are at work.

The restaurant must be compatible with the request and clear about its menu, dietary accommodations, hours, seating, and reservation options. Reviews and other third-party sources help establish credibility. And if the website lists one set of hours, Google lists another, and the online menu is two years old, consistency becomes more than a marketing issue.

It becomes a commerce issue. The AI agent may simply move on to a restaurant it can evaluate with greater confidence. And if the restaurant’s reservation platform can communicate with the AI system, the interaction can move directly from:

“This restaurant is a good fit.”

to:

“Your table is booked.”

A Handbag Manufacturer Preparing for Agentic Commerce

Now return to the laptop bag example. A handbag manufacturer may have beautiful product photography and strong brand storytelling.

A description might say:

“An elegant everyday bag designed for modern life.”

That may communicate the brand aesthetic beautifully to a person. But it gives an AI very little information to work with if the shopper wants a brown leather bag under $300 that fits a specific laptop, has an exterior pocket, offers free returns, and can arrive before a business trip.

Compare that with product information that clearly states:

Full-grain brown leather. Fits laptops up to 13 inches. Exterior zip pocket. Adjustable 20-to-24-inch strap. Weight: 2.1 pounds. Free returns within 30 days.

Now the AI has meaningful data points it can compare against what it knows about the shopper. The next layer is dynamic information. Is brown currently in stock? What is today’s price? Can it arrive before the customer’s flight? Is there a promotion? What will shipping cost?

That is where the agent moves from simply understanding the product to determining whether it is actually a viable option right now. And that information needs to remain consistent wherever the agent encounters the product.

If the manufacturer’s website says the bag fits a 13-inch laptop, one retailer says 15 inches, another marketplace listing gives no dimensions at all, and an old listing shows a discontinued color, the AI has to decide which source to trust.

The more complete, clear, credible, and consistent the product information is, the easier it is for AI to determine whether that bag belongs in the conversation.

Agentic Commerce Is Already Here

This is not entirely a future scenario. Samsung’s Bespoke refrigerators, through a partnership with Instacart, already demonstrate a version of agentic commerce inside the home. The refrigerator can use its internal camera system to recognize certain food items, help identify what may be running low, and allow the owner to reorder groceries through Instacart from the refrigerator’s screen.

Think about what has changed in that transaction. The customer did not begin by visiting Google. They did not search a grocery store website. They did not necessarily type in a product name at all. A connected system identified a potential need and helped move the customer toward a purchase.

For the brands competing for that sale, the underlying product information matters enormously. The system needs to identify the correct item, size, retailer availability, price, and other relevant details before it can confidently put the product in front of the customer. That is the broader shift businesses need to prepare for.

Agentic Commerce Readiness Starts Before the Transaction

It would be easy to assume agentic commerce only matters once AI agents are routinely completing purchases on their own, but checkout is the final step. Long before that, AI systems are increasingly involved in: researching, filtering, comparing, eliminating, ranking, and recommending products and services.

Your business can lose a potential sale before the customer ever knows you were considered. Preparing for agentic commerce therefore is not primarily about chasing the latest protocol or installing a new piece of technology. It starts by making sure AI has what it needs to answer four fundamental questions: Is this a match? Do I understand it? Can I trust it? Does everything I find support the same conclusion?

That is:

Compatibility. Clarity. Credibility. Consistency.

The AI platforms, commerce integrations, and technical protocols will continue to evolve. Those fundamentals are much less likely to change.

Is Your Business Ready for Agentic Commerce?

You do not need to know which AI platform or commerce protocol will ultimately dominate to start preparing for agentic commerce. You do need to know whether AI can accurately understand and evaluate your business today. If you are unsure how your products or services appear to AI systems, where information gaps may exist, or which of the 4 C’s may be limiting your readiness, schedule a complimentary 15-minute Explore Call. We can look at where your business stands today and determine what deserves attention first.