It feels like the way we do business online changes every few years, doesn’t it? We went from e-commerce to mobile shopping, and now we’re staring down the next big thing: agentic commerce. This is a future where smart AI agents will act for us, buying things, booking flights, and handling subscriptions, all with very little direct input. As you can probably guess, this creates a wild west of new possibilities and a whole lot of new problems.
Big names like Google, Stripe, and OpenAI are already in a sprint to write the rulebook for this new world. They’re busy building the protocols and standards that will dictate how these AI agents talk to businesses and manage our money without things going haywire.
This guide is here to cut through the noise and explain what agentic commerce standardization actually means, why it’s a huge deal for your business, and what you can start doing today to get ready for a world run by AI assistants.
What is agentic commerce?
Let’s get straight to it. Agentic commerce isn’t just a slightly smarter chatbot. It’s an AI assistant you can give a goal to, and it will figure out all the steps to get it done on its own.
Think of it like a real-life personal assistant. You wouldn’t tell your assistant, "Okay, go to Amazon, type in this specific brand of running shoes, add a size 10 to the cart, put in my credit card number, and ship it here." You’d just say, "Find me a pair of waterproof running shoes for under $150 that can be delivered by Friday." Your assistant then takes care of all the nitty-gritty research, comparisons, and the actual purchase.
That’s what an AI agent does. It takes a broad goal, breaks it down into smaller tasks, talks to different websites and systems, and wraps up the whole transaction. But for this to work smoothly and safely, all these agents need a common language to speak with business systems. And that’s where standardization comes in.
Why agentic commerce standardization is such a big deal
Without a shared set of rules, agentic commerce would be absolute chaos. Just picture thousands of different AI agents from Google, Apple, and a ton of startups all trying to talk to millions of online stores, each with its own quirky checkout process and API. It would be a complete technical meltdown. Standardization is all about solving a few core problems that would otherwise stop this whole idea dead in its tracks.
The risks of a free-for-all system
A world without standards for AI agents is pretty risky for both businesses and customers.
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Accountability and Fraud: If an agent messes up or buys something you didn’t approve, who’s on the hook? Without a clear, provable record of your instructions, figuring out what you actually intended to do becomes a nightmare. This opens the door to all sorts of disputes and gives fraudsters new ways to cause trouble.
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Data Privacy and Security: How is your payment info and personal data being kept safe as an AI agent passes it from one service to another? A lack of standards creates obvious security gaps that are just waiting to be exploited.
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Vendor Lock-in and Silos: If every AI platform has its own special way of doing things, businesses would be stuck building and maintaining dozens of separate integrations just to be seen. That’s incredibly expensive and puts smaller companies at a serious disadvantage, creating a fragmented market where only the giants can really play.
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A Terrible Customer Experience: At the end of the day, if an agent can’t reliably pull up product information, check inventory, or finish a purchase, the customer just gets annoyed. The whole promise of a seamless customer experience falls apart, and you lose a sale.
What agentic commerce standardization is trying to do
The main point of these new protocols is to build a foundation of trust and reliability. They’re trying to nail three key things:
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Establishing Trust: Creating a verifiable, cryptographic proof that a user actually said "yes" to a transaction.
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Ensuring Interoperability: Building a universal language that lets any agent communicate with any merchant, similar to how any web browser can load any website.
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Protecting Everyone: Setting clear rules for handling data, sorting out disputes, and keeping things secure for both merchants and consumers.
A breakdown of the leading agentic commerce standardization protocols
To tackle these issues, a few major frameworks have popped up, each with a slightly different angle on the problem. Here’s a quick rundown of the ones making the most waves.
Stripe & OpenAI’s agentic commerce protocol (ACP)
When a payments giant and an AI leader team up, you get a protocol that’s laser-focused on the transaction itself. ACP is all about making it super simple to turn an AI-powered discovery into an actual sale.
Imagine asking ChatGPT for a gift idea. With ACP, you could go from "What’s a good gift for a coffee lover?" to buying a specific espresso machine without ever leaving the chat. It works by creating a secure method for the AI agent to start a payment without ever handling your raw credit card details. Its primary goal is to make AI a brand-new sales channel for merchants.
Google’s agent payments protocol (AP2)
Google, along with a huge group of over 60 partners, is taking a slightly different path with AP2. They’re less concerned with the checkout flow and more focused on governance, authorization, and accountability.
AP2 uses a pretty clever system of cryptographically signed "mandates." When you tell your agent to do something (the "Intent Mandate") and then give the green light for a specific purchase (the "Cart Mandate"), AP2 creates a tamper-proof audit trail. This gives you undeniable proof of your instructions, which is a lifesaver for resolving disputes and stopping fraud. It’s really about building the legal and technical bedrock of trust for the whole ecosystem.
Open alternatives and merchant-first proposals
While the big players are getting most of the attention, other companies like Forter and Basis Theory are putting forward their own alternatives. These ideas are often designed to be more "merchant-first," giving businesses more control and making sure they don’t get pushed out of the customer relationship. These protocols usually focus on verifying the identity of the human behind the agent, which adds another layer of security and helps merchants keep that direct connection with their customers.
| Protocol/Approach | Lead Organization(s) | Primary Focus | Key Mechanism |
|---|---|---|---|
| ACP | Stripe & OpenAI | Transaction Enablement | Secure Payment Tokens |
| AP2 | Google & Consortium | Governance & Authorization | Cryptographic Mandates |
| Trusted Commerce | Forter, Basis Theory, etc. | Merchant Control & Identity | Verifiable Credentials, Open Schemas |
This video explains how the Agent Commerce Protocol (ACP) is set to revolutionize interactions, creating a new standard for agentic commerce standardization.
Beyond the transaction: The piece missing from current standardization
If you look closely at the protocols we just talked about, you’ll see they all have one thing in common: they’re almost completely obsessed with the payment. They’re solving the very important problem of how to securely finish a transaction. But a great customer experience is about so much more than just a smooth checkout.
The entire journey, both before and after the sale, is what really builds loyalty. This includes things like:
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Pre-purchase: Answering detailed questions about a product, checking if an accessory is compatible, or confirming shipping policies to a specific location.
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Post-purchase: Tracking an order, helping start a return, or troubleshooting an issue with a product.
Protocols like ACP and AP2 don’t really touch this stuff. An AI agent can’t answer, "Will this fit my 2022 model?" or "What’s your return policy for items that arrive damaged?" if it can’t tap into a business’s internal knowledge. This is the massive missing piece in the current conversation around agentic commerce standardization.
While the industry is debating payment standards, platforms like eesel AI are already tackling the knowledge problem. eesel AI works by pulling together all of a company’s scattered information, from public help centers and Shopify product pages to internal Google Docs and past support tickets in Zendesk, and makes it instantly available to an AI agent. This allows the agent to handle the entire customer journey, not just the final click to buy.
The eesel AI platform showing various integrated apps, which is key for agentic commerce standardization.How to build your agentic support capabilities today
Here’s the good news: you don’t have to sit around and wait for these global standards to be finalized to start getting the benefits of agentic AI. You can build and launch some incredibly powerful and secure AI agents for your own business right now, especially when it comes to customer support.
This is where you can get a real jump on the competition. Instead of just thinking about the transaction, you can build an agent that delivers an amazing start-to-finish experience.
Unify your knowledge in minutes
The first step is to give your agent a brain. With a tool like eesel AI, you can use one-click integrations to connect all your knowledge sources in minutes, not months. The AI doesn’t just learn from some generic script; it learns from your real business data, past customer conversations, and internal docs. This makes sure its answers are always accurate, on-brand, and actually helpful.
A view of the eesel AI platform connecting to multiple knowledge sources to prepare for agentic commerce standardization.Define what your agent can do
An agent is only truly "agentic" if it can do more than just talk. An AI that only answers questions is basically a fancy search engine. With eesel AI, you can easily set up custom actions for your agent. These can be simple tasks like tagging a support ticket or more complex workflows like looking up order info in your system, checking the status, and then reporting back to the customer. This is something the payment-focused protocols don’t even get close to addressing.
Defining agent actions in eesel AI, a crucial step for agentic commerce standardization.Go live with full control
Adopting a new global payment protocol will probably be a complex project that needs a lot of developer time. By contrast, you can get started with a platform like eesel AI completely on your own. It’s built to be self-serve. You can safely test your AI on thousands of your past tickets to see exactly how it will behave and get comfortable before you ever let it talk to a live customer. From there, you can roll it out bit by bit, giving you complete control over what your agent does and says.
The simulation mode in eesel AI helps businesses prepare for agentic commerce standardization by testing agent performance.Prepare for the agentic future
Agentic commerce standardization is a massive, and very necessary, step forward. Protocols from Google and Stripe are laying the groundwork for a future where AI-driven purchases are secure and trustworthy. But for now, their attention is almost entirely on solving the payment puzzle.
For most businesses, the bigger and more immediate opportunity isn’t at the checkout page, it’s in the entire support and knowledge layer that surrounds it. The companies that are going to win in this new era are the ones that don’t wait. They’re the ones who start building their agentic skills now by pulling their knowledge together and automating their support workflows.
Ready to build an AI agent that can do more than just take a payment? See how eesel AI can automate your support workflows in minutes. Start your free trial today.
Frequently asked questions
Agentic commerce standardization refers to the development of shared protocols and rules that enable AI agents to securely and reliably interact with various online businesses and systems. For businesses, this means ensuring their platforms can communicate effectively with AI agents to facilitate transactions and provide consistent customer experiences.
Without agentic commerce standardization, thousands of AI agents would struggle to communicate with millions of diverse online stores, leading to technical meltdowns, security risks, and a terrible customer experience. Standardization ensures interoperability, trust, and clear accountability for transactions.
Major players like Google, Stripe, and OpenAI are at the forefront. Stripe and OpenAI are developing protocols like ACP focused on transaction enablement, while Google, with its AP2, is emphasizing governance, authorization, and audit trails for agent-initiated actions.
While current agentic commerce standardization efforts largely focus on secure payment processes, the blog highlights a missing piece regarding comprehensive customer support. The broader customer journey, including detailed product inquiries, order tracking, and returns, currently relies on businesses unifying their internal knowledge bases for agents.
Businesses can start by unifying their existing knowledge scattered across various internal and external sources, like help centers and internal documents, making it accessible to AI agents. This allows agents to handle complex customer queries and support workflows beyond just processing payments.
A primary goal of agentic commerce standardization is to ensure interoperability and prevent vendor lock-in by establishing a universal language between agents and merchants. This aims to avoid a fragmented market where businesses must build numerous integrations for different AI platforms, fostering a more open ecosystem.
