Shopping online has traditionally meant doing the work yourself. You search for a product, compare prices, read reviews, add an item to your cart, and complete the payment. But AI agents are starting to change that. Instead of navigating dozens of websites on their own, shoppers can increasingly rely on AI to find products, compare options, make decisions, and even help complete purchases.
That shift is at the heart of agentic commerce: a model of ecommerce where AI agents can act on a shopper’s behalf across parts of the buying journey.
And as these agents become more capable, a new question is emerging for brands and ecommerce teams: how exactly should AI agents interact with online stores and payments?
That’s where standards such as ACP, AP2, and UCP come in.
In this guide, we’ll break down ACP vs AP2 vs UCP, what each standard does, how they differ, and what they could mean for marketing, ecommerce, and the way brands reach customers as AI agents become part of the buying process.
ACP vs AP2 vs UCP: Quick Comparison
| Standard | Primary purpose | Main players | Where it sits | Best understood as |
| ACP | Agent-led commerce and checkout | OpenAI + Stripe | Commerce layer | A way for AI agents and businesses to connect across the commerce journey |
| AP2 | Agent payment authorization and security | Google + ecosystem partners | Payment layer | A framework for proving and enforcing a user’s intent when an agent makes a payment |
| UCP | Standardized commerce workflows | Google + Shopify + ecosystem | Commerce layer | A common framework covering commerce flows from discovery and checkout through orders and post-purchase |
| Bottom line | — | — | — | ACP and UCP overlap most closely; AP2 addresses the authorization and payment side and can work alongside commerce protocols |
A simple way to think about the difference is:
UCP or ACP can help an agent figure out what to buy and complete the commerce workflow. AP2 helps establish that the agent is authorized to pay for it.
In an agentic commerce ecosystem, these standards can potentially work together rather than compete directly.
What is ACP in Agentic Commerce?
The Agentic Commerce Protocol (ACP) is an open standard developed by OpenAI and Stripe to help AI agents and businesses work together during online commerce.
The idea is simple: instead of making every AI platform and merchant build a separate connection, ACP provides a shared way for them to communicate. A merchant can make product, pricing, checkout, and order information available in a format that an AI agent can work with, while still keeping control of its backend systems, fulfilment, and customer relationship.
That makes ACP less about replacing a merchant’s existing ecommerce infrastructure and more about making that infrastructure accessible to AI-driven shopping experiences.
And that role is becoming even more important as AI moves further upstream in the buying journey.
What ACP Means for Marketers
In March 2026, OpenAI expanded ACP to support richer product discovery in ChatGPT. Merchants can share product feeds and promotions so their catalogs can be represented more completely and accurately in AI-driven shopping experiences. OpenAI says ACP is being used to connect merchants and users throughout discovery, with future applications including personalization, local availability, and delivery estimates.
That creates a few practical considerations for marketing teams.
Product information needs to be AI-ready.
If an AI agent is helping someone decide what to buy, it needs reliable information about the product. Names, descriptions, attributes, pricing, availability, promotions, and other catalog details all become part of the information an agent uses to understand and surface an offering.
Discoverability is no longer limited to traditional search.
A customer may not search Google for “best running shoes under $100” and then visit ten ecommerce sites. They may ask an AI assistant the same question and expect it to compare products for them. That means marketers need to think about how clearly their product information can be understood and surfaced in AI-driven experiences.
The gap between discovery and purchase is getting smaller.
ACP was initially launched around Instant Checkout, where ChatGPT could take a shopper from product discovery to purchase within the conversation. As AI shopping experiences evolve, that tighter connection between finding a product and buying it could reduce the number of steps between consideration and conversion.
Accuracy matters more.
If an AI agent is comparing products for a customer, outdated pricing or incorrect availability can quickly make a recommendation less useful. For ecommerce teams, maintaining accurate and up-to-date product information therefore becomes even more important.
Where Does ACP Stand Today?
When OpenAI and Stripe introduced ACP in 2025, the emphasis was on enabling programmatic commerce flows and supporting purchases through experiences such as Instant Checkout.
Today, ACP is also being positioned as a connective layer for product discovery. OpenAI’s March 2026 update specifically describes ACP as a way to connect merchants and users throughout discovery, with product feeds and promotions helping bring richer, more current catalog information into ChatGPT.
So it would be misleading to frame ACP as either a failed checkout standard or something that has simply been replaced. Its role is evolving alongside the broader agentic commerce ecosystem.
For marketers, the more useful question is whether AI assistants will become an increasingly important product-discovery channel. If they do, standards such as ACP could influence how brands make their catalogs visible and understandable to those AI systems.
What is AP2?
Agent Payments Protocol (AP2) is designed to solve one of the biggest problems with agentic commerce: how do you know that an AI agent is actually authorized to make a purchase on someone’s behalf?
An AI agent can find a product, compare options, and build a cart in seconds. But when it comes time to spend money, simply knowing what the agent did isn’t enough. Merchants and payment providers also need to know what the customer actually intended to authorize.
That’s the problem AP2 addresses.
Developed by Google with ecosystem partners, AP2 provides a framework for verifiable payment authorization when agents act on behalf of users. Rather than treating an agent’s action as sufficient proof of consent, it creates a record that connects the user’s intent, the transaction being authorized, and the eventual payment.
In other words, while a commerce protocol can help an agent figure out what to buy and where to buy it, AP2 focuses on establishing whether the agent is actually authorized to make that purchase.
How Does AP2 Work?
At a high level, AP2 uses a series of mandates to create a verifiable trail from intent to payment.
User intent
First, there needs to be a clear record of what the user wants the agent to do. This can include things such as the product or service, merchant restrictions, spending limits, or other conditions.
This is captured through an IntentMandate, which establishes the user’s instructions and the boundaries within which an agent can act.
Cart authorization
Once an agent reaches a specific purchase, the merchant can provide a CartMandate containing the details of the proposed transaction. This can include the items, price, merchant, and other checkout information, along with a merchant signature.
Think of this as the merchant saying, “This is exactly what we’re offering, at this price.”
Payment authorization
The next step is the PaymentMandate, which authorizes the actual payment and connects it back to the transaction details.
This creates a much clearer distinction between an agent finding or preparing a purchase and the customer actually authorizing money to be spent.
A verifiable trail
Together, these steps create an auditable chain connecting what the user intended, what the merchant offered, and what payment was ultimately authorized.
That’s particularly important when AI agents are making decisions or taking actions with less human intervention. AP2’s use of cryptographically verifiable mandates is intended to make that authorization trail harder to dispute or manipulate.
What AP2 Means for Marketers
For marketers, AP2 could matter in several ways.
Greater confidence in agent-led purchases
Consumers may be more comfortable allowing AI agents to make purchases when there are clearer boundaries around what those agents are allowed to do and when their actions can be verified.
A clearer connection between intent and conversion
Traditional ecommerce already tracks the path from product view to cart to purchase. Agentic commerce adds another layer: an AI may be the one making recommendations, selecting products, or initiating the transaction. AP2 helps establish what the customer actually authorized within that process.
New considerations around promotions and recommendations
If an agent is making purchasing decisions based on product information, offers, prices, or other conditions, marketers will need to think carefully about how those inputs translate into an authorized transaction. A promotion that is visible to an agent, for example, needs to be accurately represented when the purchase is actually made.
Less friction without removing control
The long-term promise of agentic commerce is that customers won’t need to manually complete every step of a purchase. AP2 is part of the infrastructure that could make that automation possible while still maintaining clear authorization boundaries.
What is UCP?
The Universal Commerce Protocol (UCP) is an open standard developed by Google and Shopify to give AI agents and businesses a common way to interact across the commerce journey.
It aims to standardize the different steps an agent may need to handle when helping someone buy something. That can include:
- Product discovery: Helping agents find relevant products and merchants.
- Catalog and product information: Making product details available in a standardized format.
- Inventory: Communicating whether products are available.
- Cart: Managing items selected for purchase.
- Checkout: Supporting the process of completing a transaction.
- Order management: Handling information about orders after checkout.
- Fulfillment: Connecting the commerce experience with delivery and fulfillment processes.
- Post-purchase interactions: Supporting actions such as order updates and other customer-service interactions.
The idea is to give AI agents a more consistent way to interact with different businesses instead of requiring every agent and merchant to build a completely separate integration.
Why UCP Matters for Marketers
UCP isn’t just about making the technical side of agentic commerce easier. It could change how products are discovered, evaluated, and purchased in the first place.
Product discoverability could extend beyond traditional search.
As AI agents become part of the shopping journey, customers may increasingly ask an agent to find products instead of navigating ecommerce websites themselves. UCP is designed to give those agents standardized ways to interact with commerce data and capabilities.
Product feeds become increasingly important.
An agent needs structured, reliable information to make useful recommendations. Product names, descriptions, attributes, prices, availability, promotions, and other catalog information can all influence how an offering is represented within an AI-driven shopping experience.
Pricing and availability need to stay accurate.
In an agent-led shopping journey, inaccurate product information can affect more than the customer experience. It can influence whether a product is recommended in the first place.
Conversion paths could become much shorter.
Traditional ecommerce often takes a customer through a sequence of search, website visit, product page, cart, checkout, and confirmation.
With agentic commerce, some of those steps can happen through the agent itself. The customer might describe what they want, review a few recommendations, and move toward checkout without manually navigating several websites.
Merchant-controlled data still matters.
UCP does not mean that every brand needs to hand its entire commerce operation over to a central marketplace. The protocol is designed to connect AI agents with merchant capabilities and data while allowing businesses to connect using their existing commerce systems.
That distinction matters because brands still need control over the information representing their products: what is available, how it is priced, which promotions apply, and how orders are fulfilled.
UCP’s Distributed Approach
UCP provides a standardized way for agents to interact with commerce capabilities that remain connected to the merchant’s own systems. A business can expose relevant products, inventory, checkout, order, and other commerce functionality without having to replace its existing infrastructure.
Your product information becomes something AI agents can interact with directly, rather than something customers can only discover by manually navigating your website.
Today, a catalog primarily helps a customer understand what a business sells. In an agentic commerce environment, that same catalog may also become the source an AI agent uses to understand what a business can offer, compare it with alternatives, and potentially move the customer toward purchase.
ACP vs AP2 vs UCP: What’s Actually Different?
The simplest way to understand the difference is to look at which part of the buying journey each one is designed to handle.
Primary Purpose
| Standard | Primary purpose |
| ACP | Agent-led commerce and product discovery |
| AP2 | Payment authorization and verifiable user intent |
| UCP | Standardizing the broader, end-to-end commerce workflow |
Where Each Sits in the Agentic Commerce Stack
A simplified view looks like this:
AI model/agent
↓
Tool & data access → MCP
↓
Discovery & Commerce workflow → ACP/UCP
↓
Payment Authorization → AP2
↓
Transaction
There can be overlap between ACP and UCP because both can support agent-to-business commerce interactions. AP2 sits at a different layer, dealing with authorization rather than the broader commerce workflow.
It’s also worth separating these from MCP, which can sit underneath agentic systems as a tool and data-access layer. MCP can help an agent access external tools or information, while protocols such as ACP, AP2, and UCP address specific aspects of how agentic commerce works.
Who is Driving Each Standard?
| Standard | Key organization |
| ACP | OpenAI + Stripe |
| AP2 | Google + ecosystem partners |
| UCP | Google + Shopify |
What Marketers Should Care About?
| Marketer concern | ACP | AP2 | UCP |
| Product discovery | High | Low | High |
| AI shopping | High | Medium | High |
| Checkout | Relevant | High | High |
| Payment authorization | Low | Core | Supporting |
| Product data | High | Low | High |
| Inventory/availability | Relevant | Low | Core |
| Post-purchase commerce | Limited | Low | Strong |
| Marketing readiness | High | Medium | High |
Which Agentic Commerce Standard Should Marketers Watch?
| If your priority is… | Watch | Why it matters |
| AI product discovery | ACP | Strong connection to OpenAI, ChatGPT, and AI-driven product and commerce experiences. |
| Secure agent payments | AP2 | Focuses on payment authorization and establishing that an AI agent is authorized to transact on a user’s behalf. |
| Broader ecommerce operations | UCP | Covers a wider commerce journey, including product information, inventory, cart, checkout, orders, fulfillment, and post-purchase interactions. |
| Long-term agentic commerce strategy | All three | Each addresses a different part of the agentic commerce stack, so marketers should track adoption, ecosystem participation, and real-world use cases rather than pick a single winner. |
Agentic commerce isn’t one protocol. It’s an ecosystem of connected layers that collectively move an agent from understanding a customer’s request to helping complete a transaction.
Agentic commerce is evolving quickly, and these protocols are only one part of the bigger shift. Check out our other guides on the topic:
- What is the Agentic Commerce Protocol (ACP)? A Marketer’s Guide
- From Prompts to Pipelines: How Agentic AI Workflows Are Replacing Manual Marketing Tasks
- How to Optimize Your Website for AI Agents: A Complete Setup Guide
FAQs
Yes. ACP and UCP can be complementary, although they have overlapping areas. ACP focuses strongly on agent-led commerce and discovery, while UCP covers a broader set of commerce workflows, including product discovery, checkout, orders, and post-purchase interactions.
Yes. AP2 focuses on payment authorization rather than the broader commerce workflow. It can work alongside commerce protocols such as UCP to add verifiable authorization when an AI agent makes a payment.
MCP sits further down the stack. It gives AI agents a standardized way to access tools and data, while ACP and UCP handle commerce interactions. In simpler terms, MCP helps the agent access capabilities, while commerce protocols help it use those capabilities in a buying journey.
A2A (Agent2Agent) is designed for communication between AI agents and agentic systems. It can support collaboration between agents, while protocols such as ACP and UCP focus specifically on commerce interactions. A2A is therefore supporting infrastructure rather than a direct alternative to these commerce standards.
Mostly complementary. ACP and UCP have the most overlap because both address agentic commerce, while AP2 focuses on payment authorization. MCP and A2A sit in supporting layers. The broader ecosystem is likely to involve multiple protocols working together rather than one replacing all the others.
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