Agentic AI Payment Standards: The Future of Autonomous Shopping

Imagine this: Your AI assistant finds you the perfect pair of running shoes at a great price, and instead of sending you a link, it checks out on your behalf while you sip your coffee. Today, that scenario is almost possible – AI agents can browse and recommend products, but they hit a wall at the final step: payment. Right now, even ChatGPT’s shopping feature will ultimately nudge you to click through to the retailer’s site and manually enter your payment details. The next leap in e-commerce is to let AI agents securely complete purchases for users, ushering in the era of fully autonomous shoppingventurebeat.com. Achieving that means establishing new agentic payment standards so that merchants, banks, and consumers can trust an AI to “click the buy button” on our behalf. In late 2025, we’ve seen a flurry of initiatives to make this a reality, led by industry heavyweights like Google, OpenAI/Stripe, and Visa. This article dives into why these new standards are needed, what the leading proposals – AP2, ACP, and TAP – are all about, how they compare, and what mid-market merchants should be doing now to prepare.

Why Do We Need New Payment Standards for AI?

The short answer: Existing online payment flows assume a human is in control. Today’s fraud checks and authentication steps – entering a CVV code, one-time passwords via text, 3-D Secure pop-ups from your bank – all presume a human is there to respond. These are our guardrails; for example, a bank might text you a code to confirm it’s really you making a purchase. But if an AI agent is initiating the checkout, those human-centric guardrails don’t fit. How does an AI “know” your card’s CVV, or retrieve an OTP from your SMS? More critically, how do you (or your bank) know that an AI’s attempt to pay is something you actually authorized, not a bot going rogue? The truth is, right now people and banks simply don’t feel safe letting a bot loose with their credit card.

From the consumer side, there’s understandable fear: “Did my virtual assistant just buy something I didn’t want?” From the merchant and financial side, there’s fear of fraud: a surge of chargebacks from customers saying “that wasn’t me” could wreak havoc if AI agents start checking out without proper authorization trails. In short, if we want AI-driven commerce, we need a common language of trust between the AI agent, the user, the merchant, and the payment networks. This would assure everyone that an agent’s transaction is legitimately authorized and executed as intended.

That’s exactly what the new agentic payment standards aim to do. Over the past few weeks (as of late October 2025) several major players announced protocols for “agent checkout” – essentially new standards to let AI assistants pay for things on behalf of users in a secure, verifiable way. Think of these like the next generation of checkout APIs, with built-in safeguards and audit trails for AI-driven orders. Let’s explore the three leading contenders and how they tackle the trust gap.

The Contenders: AP2, ACP, and TAP

Multiple proposals have emerged, but three stand out, backed by different camps:

• AP2 (Agent Payments Protocol) – led by Google Cloud in a broad coalition including Adobe, PayPal, American Express, Mastercard, Salesforce, and many others.

• ACP (Agentic Commerce Protocol) – introduced by OpenAI in partnership with Stripe (with Shopify and Salesforce among early supporters).

• TAP (Trusted Agent Protocol) – launched by Visa, leveraging its card network expertise (Mastercard announced a similar initiative alongside Visa.

Each of these aims to become the standard that agents, merchants, and payment providers all adopt. It’s a bit of a VHS vs. Betamax moment for AI commerce (or perhaps more like the early days of mobile wallets where each platform had its own approach). Below we break down what each protocol is and how it works.

AP2 – Agent Payments Protocol

Who’s behind it: Google Cloud spearheaded AP2, assembling a “big tent” alliance of over 60 organizations at launchv. Major payment networks (Mastercard, Amex, JCB, UnionPay), processors (PayPal, Worldpay, Adyen), banks/fintechs (Intuit, Revolut, Coinbase), commerce platforms (Adobe/Magento, Salesforce), and more are on board. This strong backing indicates AP2 may go through formal standards bodies, aiming to be a truly universal standard to avoid fragmentation.

Core idea: AP2 introduces the concept of digital “Mandates” as the trust mechanism. A Mandate is essentially a tamper-proof, cryptographically signed digital contract of what the user has authorized. For each agent-driven purchase, there are typically two mandates:

• An Intent Mandate – capturing the user’s instruction in a human-readable and machine-verifiable form. e.g. “User Alice permits her agent to buy a pair of green running shoes, up to $100, from any reputable store.” This is signed with the user’s credentials (or a key on their behalf), creating a record of consent.

• A Cart (or Purchase) Mandate – representing the final transaction details the user approved, like “Purchasing SuperBrand Green Running Shoes from ShopXYZ for $89 including tax”. This is created once the agent has compiled the order and the user confirms. It’s also digitally signed and locked.

These mandates travel with the payment request as attached data. Anyone in the payment chain can verify them – the merchant, the payment processor, the bank – to be sure the AI’s transaction aligns with a real user instruction. In effect, AP2 provides cryptographic proof that “this purchase was authorized by the user (and here’s the evidence of what they asked for)” which addresses the big concerns of authorization and liability. If there’s a dispute, the mandates serve as an audit trail of who said what.

Crucially, AP2 is payment-method agnostic and very flexible. It’s designed to work with credit/debit cards, bank transfers, digital wallets, even crypto payments via extensions. For instance, Google and partners developed an extension (x402) to handle stablecoin crypto transactions under the AP2 framework. The goal is that AP2 can ride atop any payment rail as a trust layer.

Because it’s an open protocol with open-source reference implementations on GitHub, any developer or platform can start experimenting. However, AP2’s focus on security and verification means it’s somewhat complex to implement from scratch. It involves managing cryptographic keys and verifying signatures/mandates at various points. In practice, we expect e-commerce platforms and payment gateways to bake in AP2 support over time (Adobe’s Magento, for example, is part of the coalition, so they may release updates to support AP2 natively). Early adopters could pilot it themselves, but it’s a heavier lift than the other protocols discussed below.

Why merchants might care: AP2 offers the strongest assurance and auditability. It’s like getting a notarized letter of consent with every AI purchase. This could be valuable for high-value orders, regulated industries, or any scenario where disputes would be costly. It’s also a coalition-driven, openly governed approach, meaning it’s less likely to be proprietary or pay-to-play. If you’re worried about one vendor (say, OpenAI or Visa) controlling the standards, AP2’s design is meant to stay neutral and interoperable. On the flip side, it might take longer to see AP2 in widespread use, since it requires coordination among many players to implement and roll out.

ACP – Agentic Commerce Protocol

Who’s behind it: ACP was unveiled by OpenAI in partnership with Stripe and debuted in September 2025 as the backbone of ChatGPT’s new “Instant Checkout” feature. It’s open-sourced (available at agenticcommerce.dev) and supported by initial partners like Shopify and Salesforce Commerce Cloud. In fact, OpenAI has already piloted ACP in the real world: U.S. ChatGPT users can now buy products from Etsy sellers entirely within ChatGPT, with Shopify merchants next in line. This immediacy gives ACP a head start in practical adoption.

Core idea: ACP focuses on simplicity and rapid integration for merchants. Rather than reinventing the wheel, it uses a familiar web paradigm: an API-based checkout workflow between the AI agent and the merchant’s backend. In essence, the AI agent acts like a front-end client (similar to a browser or mobile app) that talks to your store’s server to create an order. The difference is the customer is guiding the agent via chat, not clicking your website’s UI.

Here’s how a typical ACP-powered transaction works:

1. Product Discovery: The AI (e.g., ChatGPT) has access to a Product Feed from the merchant that lists products with prices, stock, etc. This feed is kept up-to-date (pulled regularly) so the AI knows what’s available and avoids suggesting out-of-stock items.

2. Initiate Order: When the user is ready to buy, the AI calls the merchant’s checkout API – specifically a POST /checkout_sessions endpoint – sending the desired items and user details. The merchant’s server responds with a session ID and a summary of the cart (prices, any shipping options, etc.).

3. Update Cart: As the agent collects more info (shipping address, shipping method, etc.), it calls POST /checkout_sessions/{id} to update the session. The merchant backend recalculates totals (tax, shipping) and returns updated cart.

4. Complete Order: Finally, the agent calls the .../complete endpoint for that session when the user confirms. At this step, a payment token is passed to the merchant, and the merchant’s backend processes the payment through its usual processor, creates the order in its database, and returns an order confirmation or error.

The payment part uses a “delegated payment” approach. The AI agent never handles raw credit card numbers. Instead, the user’s payment info (which could be on file with ChatGPT or entered securely) is converted into a token that represents the payment. For instance, Stripe generates a Shared Payment Token (SPT) that is scoped to that specific merchant and order amount. ChatGPT (the agent) passes this token to the merchant’s complete-order API. The merchant then either charges that token via Stripe (if they are a Stripe user) or, if they use another gateway, they can forward the token to Stripe for verification while completing the charge on their own systems. This way, merchants retain their existing payment processor and flow – they just accept a token instead of a card number. Stripe has made it especially easy for its merchants: enabling agent payments can require as little as one line of code using Stripe’s libraries. For non-Stripe merchants, ACP’s spec is open so that other payment providers (Adyen, PayPal, etc.) could issue and accept compatible tokens in the future.

In simpler terms, ACP treats the AI agent as a new sales channel or front-end. It’s akin to a conversational marketplace: ChatGPT becomes a shopping platform where many merchants can list products and transact, but each sale is ultimately between the user and the merchant (ChatGPT is just facilitating). Merchants remain the merchant-of-record – they handle fulfillment, returns, and customer service just like a normal order. They also get the customer details and order in their system, and they can maintain their relationship with the buyer. This is an important design choice: unlike selling through, say, Amazon (where Amazon controls the customer data and experience), selling through ChatGPT via ACP lets the merchant keep control. As Shopify’s team put it, merchants stay front and center – their brand is shown to the shopper and orders flow into their normal admin with full attribution.

Why merchants might care: ACP’s big advantage is speed to market and low implementation friction. If you’re on a platform like Shopify or Salesforce, much of it may be handled for you at the platform level. Shopify, for example, announced that its merchants will be automatically able to participate in ChatGPT’s Instant Checkout (with an option to opt-out) – effectively turning it on by default for millions of stores. If you run on Magento/Adobe Commerce or another custom platform, you can integrate ACP by following the open documentation: essentially setting up a feed and a handful of REST endpoints. Several solution providers have already published guides and even plugins to help with this. In other words, ACP offers a quick win – it’s already bringing real sales via ChatGPT, and merchants can jump on board with relatively minimal development compared to the other standards.

However, ACP is initially tied to OpenAI’s ecosystem (ChatGPT). It’s open-source, so in theory other AI platforms could use it, but the momentum is with ChatGPT as the first mover. Also, because it doesn’t introduce heavy new authentication measures (it leverages existing payment tokenization and fraud checks), some might consider it a bit less “bulletproof” on the security/audit front compared to AP2. Essentially, it relies on the fact that the user’s card is tokenized with a trusted processor and that the merchant still has final say (they can accept or reject the order, just like any order they get). For most consumer retail scenarios, this is fine – especially given Stripe’s fraud detection and the user having to confirm the purchase in chat. But ACP isn’t (at least yet) trying to solve edge cases like fully autonomous purchases without user confirmation, or multi-network payments; it’s focused on getting real transactions working now in a user-friendly way.

TAP – Trusted Agent Protocol

Who’s behind it: TAP is the entry from Visa, announced in mid-October 2025 as part of Visa’s push to make card payments “agent-friendly.” Visa basically said, “if AI agents are going to shop, we want them using Visa cards – and we want to make sure that’s safe for everyone.” While AP2 is more platform-agnostic and ACP is tied to ChatGPT, TAP is card-network-centric. (Mastercard, notably, launched its own Agent Pay framework around the same time, and it’s aligning with broader efforts too. We’ll focus on Visa’s TAP as the exemplar.)

Core idea: TAP extends the existing credit card infrastructure to explicitly recognize and trust AI agents. Think of how “Verified by Visa” (or Visa Secure) works – it’s a system to authenticate the human cardholder during online purchases. TAP similarly aims to authenticate the AI agent acting on behalf of the cardholder.

In TAP’s model, an AI shopping agent would be issued a sort of digital ID or certificate by Visa. This would likely involve the agent platform registering with Visa and obtaining cryptographic credentials. As a user, you might approve certain AI agents to use your card – essentially adding them to an “approved agents” list on your card account. Then, when an agent initiates a purchase with your Visa card, it would sign the transaction with its unique digital key. Visa’s network (and by extension, the merchant’s payment gateway) can verify that signature to confirm:

1. This transaction is coming from a known, trusted agent.

2. That agent is authorized by the user (cardholder) to use their card.

All of this happens behind the scenes in split seconds as the payment is processed. From the merchant’s perspective, the beauty of TAP is that it requires little to no change on the checkout flow. If your payment gateway or processor supports TAP, the agent’s identity data comes through the normal payment authorization messages. Visa’s systems handle the verification in the background. The merchant just gets a response like “Approved (Agent XYZ verified)”. In other words, no new APIs for merchants – it’s baked into the card payment rails. Visa has stated that their goal is to give merchants clarity on agent-initiated transactions “without requiring them to overhaul their systems”.

One way to think of TAP is like giving your AI assistant its own virtual credit card (with strict controls). For example, I might authorize “ShoppingAgent GPT” to use a tokenized version of my Visa card for purchases up to $500. The first time that agent tries a transaction, Visa knows it’s associated with my account and checks my approval. The transaction request includes a cryptographic signature proving it’s really “ShoppingAgent GPT” and not an imposter bot. Visa’s network approves the charge, and the merchant processes it as usual. If something looks off (say the agent tries a $5,000 charge or an unapproved agent attempts to pay), the network can decline or flag it – similar to how fraud rules work today, but now with agent identity in the mix.

Why merchants might care: In the near term, you can’t directly implement TAP as a merchant – it will roll out via the payment networks and acquirers. But if it succeeds, TAP could make agent-based purchases feel just like normal card transactions to you, with the extra assurance that the card network has verified the agent. It’s a promising approach for reducing fraud and false declines. For instance, today a bot trying your card might trigger a decline as suspected fraud; with TAP, a legitimate agent transaction could be recognized and approved more smoothly, while illegitimate ones get blocked. Visa is positioning TAP as a no-code solution for merchants (nothing new to integrate) which is appealing.

However, TAP (and Mastercard’s similar effort) is limited in scope – it’s only for card payments, and initially only one network’s cards. It’s a more closed ecosystem at the start: if a user’s preferred payment is a bank transfer or a PayPal account, TAP doesn’t address that. That’s where something like AP2 (covering multiple payment types) or ACP (processor-agnostic) might fill in. Visa has indicated it’s aligning TAP with broader standards (they explicitly mentioned working with OpenAI’s ACP and even Coinbase’s crypto standard) to ensure compatibility. So, we might see TAP as one piece of a larger puzzle, rather than a standalone silo.

Now that we’ve outlined the three main standards, let’s compare their approaches on a few key dimensions.

Comparing AP2 vs. ACP vs. TAP

Each protocol takes a different route to solve the same fundamental problem (trustworthy AI-driven payments). Here’s how they stack up:

• Trust & Security Mechanism: AP2 relies on per-transaction cryptographic proofs called Mandates – effectively a detailed signed record of the user’s intent and approval for each purchase. TAP also uses cryptography, but at the agent identity level – an agent must present a verifiable credential/signature to prove it’s trusted by the user for the card being used. In contrast, ACP uses a more conventional security approach: an API handshake and tokenized payments. The agent passes an encrypted payment token and the merchant relies on existing fraud controls of the payment processor. There’s no new crypto signature in ACP (beyond what payment gateways already do); it trusts the fact that the user authenticated with ChatGPT and explicitly confirmed the order, and the payment processor handles the rest. In summary, AP2/TAP create new cryptographic trust signals (more robust audit trail), while ACP leverages existing trust frameworks (faster to implement).

• Scope and Openness: AP2 aims to cover all payment types and many use cases – consumer retail, B2B procurement, even agent-to-agent transactions. It’s meant to be a broad industry standard not tied to any single platform. ACP is currently focused on retail e-commerce via AI chat – basically helping people buy physical or digital goods from online stores through a chat interface. It’s an open spec, but so far its real-world use is within OpenAI’s ChatGPT ecosystem (which could expand to others). TAP is specific to card payments (Visa for now) and is controlled by a single network (though one with huge reach). If we imagine the future: AP2 could be the most interoperable (any agent with any payment method), ACP could be the most pragmatic for quick deployment in shopping assistants, and TAP could be one piece of the puzzle that eventually integrates into these others (Visa has signaled it doesn’t want to conflict with AP2 or ACP but complement them).

• Ease of Merchant Adoption: For merchants, ACP is the clear winner in the short term. If you use Shopify, ChatGPT shopping may “just work” for you with minimal setup. If you use Stripe, enabling ACP is trivial with their tools. Even on other platforms, implementing ACP is akin to adding a new checkout integration – not trivial, but many have done it already with guides and some open-source modules available. AP2, on the other hand, will likely arrive via updates from platforms or payment providers down the road. You could implement AP2 now using the open spec, but you’d be building a lot of new infrastructure (storing/verifying mandates, integrating with your payment flow) largely on your own. It’s more realistic to keep an eye out for your e-commerce platform or gateway to announce AP2 support. TAP, as noted, doesn’t require you to do anything except maybe toggle it on when your processor supports it. But as of late 2025, it’s in pilot stages – you might not see any effect until your acquirer or gateway rolls it out network-wide.

• Walled Garden vs. Open Ecosystem: A concern with competing standards is the risk of fragmentation – e.g., what if one set of customers uses only Google’s ecosystem (AP2) and another uses only ChatGPT (ACP)? Would a merchant have to implement multiple systems to cover both? The industry is mindful of this. Google explicitly launched AP2 to prevent a fragmented, walled-garden scenario by being open and inviting everyone to collaborate. OpenAI open-sourced ACP for similar reasons, but let’s be frank: ACP in practice ties participants to OpenAI/Stripe’s orbit, at least initially. Visa’s TAP is by nature tied to Visa’s network. In the worst case, yes, merchants might end up juggling 2-3 standards if different user bases gravitate to different AI platforms (just like some shoppers prefer Amazon Pay vs Apple Pay vs PayPal – many sites now offer all of the above). The hopeful view is that over time these standards will converge or interoperate. In fact, some experts predict a single winning standard or a hybrid that takes the best of each approach could emerge in a few years. Already, we see Visa saying they’ll align TAP with OpenAI’s ACP, and Mastercard partnering to ensure consistency. For now, enterprises might need to experiment with all and see which gains traction. The good news is all three are being presented as “open” in some way, so it’s not like any of them are completely closed proprietary systems – they just have different backers and starting points.

• Ideal Use Cases / Strengths: We touched on this, but to summarize: AP2 is like a fortified truck – heavy-duty, secure, suited for high-stakes scenarios (think expensive purchases, regulated purchases, or complex multi-party commerce where audit trail is king). ACP is the nimble sports car – quick to get on the road, great for the common retail use case of “chatbot recommends item, user buys it now,” and likely to drive early revenue for merchants who adopt it. TAP (and similar network solutions) is more like an upgrade to the highway – invisible to the driver (merchant or user) but making the journey safer and smoother when using that route (Visa cards). Large enterprises will likely support multiple of these if they all stick around: e.g., an online retailer might accept ACP orders via ChatGPT, AP2 orders via a Google Assistant or other agent, and rely on TAP in the background for card transactions. That sounds messy, but it may be the reality until standards unify.

How Can Merchants Prepare Today?

If you’re leading an e-commerce team, especially in the mid-market, you might be wondering: Do I need to do anything about this now? The holiday season is here, you have conversion and fulfillment to worry about – is “agentic commerce” something to tackle immediately or just watch for now? Here’s a practical game plan:

• Stay Informed on Developments: First, keep a finger on the pulse. The landscape is evolving literally week by week. Big tech and payment companies are racing here, and today’s front-runner could change. Subscribe to industry news (the VentureBeat articles, Google Cloud blog posts, OpenAI updates, etc.), and perhaps join any developer communities or webinars about these protocols. For example, Google has the AP2 spec on GitHub – have your technical architect at least read the overview. OpenAI has documentation and an application form for merchants interested in ChatGPT’s Instant Checkout. Being knowledgeable will help you make timely decisions and impress stakeholders that you’re ahead of the curve.

• Assess Your Platform & Partnerships: What e-commerce platform are you on, and who are your payment providers? This will influence your approach:

  • If you’re on Shopify – good news, Shopify is actively working with OpenAI. You likely will be automatically enabled for ACP/ChatGPT sales soon (if not already). Ensure you’ve reviewed Shopify’s announcements and any settings you might need to toggle. Mostly, focus on your product data (more on that below) because Shopify will handle a lot of the integration for you.

  • If you’re on Adobe Commerce/Magento or another custom platform – you have the opportunity to implement ACP yourself. Adobe hasn’t released an official module as of Oct 2025, but the protocol is open. Teams like Magebit (a Magento agency) have published guides and even modules to help integrate ACP now. You could start with a proof-of-concept: maybe enable a small category of products or a test store to trial ChatGPT Instant Checkout. This hands-on experience is invaluable, even if volume is low at first. Also keep in touch with Adobe – since they’re part of the AP2 coalition, watch for Magento updates that might include AP2 support down the line.

  • For other platforms (Salesforce Commerce, etc.) – check if your provider has announced anything. Salesforce, for instance, has hinted at integrating ACP via its Commerce Cloud (and through a thing called “Agentforce”). If your platform has a user group or community, see what others are doing. In absence of official support, consider building the integration with your dev team or a partner agency.

  • Talk to your payment processors/acquirers as well. Ask your Stripe rep or PayPal account manager or bank contact: “Are you planning to support agent-initiated payments or these new protocols?” Their answers might guide your strategy. For example, if Adyen (your PSP) says “we’re working with Google on AP2 pilots,” you could volunteer your site as a tester.

• Get Your Data and Systems “Agent-Ready”: All the fancy AI in the world won’t help if your basic e-commerce data is messy or your site can’t handle automated interactions. Now is the time to shore up the fundamentals:

  • Product Data Accuracy: Ensure your product catalog data (titles, descriptions, pricing, inventory levels) is clean and up-to-date at all times. AI agents rely on feeds – if your feed shows a product in stock at $50 but it’s actually out of stock or $70, the agent’s attempt to buy will fail or be wrong. That’s a bad user experience and could cause the AI to distrust recommending your store. Focus on real-time inventory sync and pricing accuracy. If you haven’t already, implement structured data (like JSON-LD) on your site and robust product feeds (similar to Google Shopping feeds).

  • Robust Checkout & Order APIs: Agents will be hitting your endpoints quickly and maybe frequently. Make sure your checkout process can handle being driven via API. This includes proper idempotency (so duplicate calls don’t create two orders) and error handling (gracefully handle if an item goes out of stock during a session, etc.). If you don’t have an API for checkout yet, consider building one (even aside from AI, a checkout API is useful for headless commerce or mobile apps).

  • Payment Processor Readiness: If you use Stripe, look into enabling the Shared Payment Token. If you use another provider, see if they have sandbox support for token-based payments or if you could route agent orders through Stripe as a stopgap. The idea is to be comfortable processing an order where payment comes via token, not via your usual front-end form.

  • Fulfillment and Customer Service: AI-originated orders should flow into your system like normal, but be prepared for edge cases. For instance, what if a user claims “the AI ordered the wrong item”? How will you handle returns or disputes? It might be no different than usual (a return is a return), but consider adding a flag for agent-driven orders in your system. That way your team knows if an order was placed via ChatGPT or another agent and can gather any unique insights (was the issue due to miscommunication with the AI?). Having analytics to tag and track “agentic orders” will help you measure this new channel’s performance.

• Start Small – Pilot and Learn: You don’t have to bet the farm on one of these standards yet, but it’s wise to experiment in a controlled way:

  • If you can, join a beta or pilot. OpenAI had an application for merchants to get into the ChatGPT shopping program – apply there. Google’s AP2 is open source; maybe have a developer try to simulate an AP2 transaction in a test environment to see what the data looks like. Visa’s TAP might be harder to test without being in their program, but you could reach out to your Visa reps.

  • Use sandbox modes. For ACP, you could use Stripe’s test mode to run through an end-to-end Instant Checkout flow (OpenAI provided sandbox credentials for developers). This will let you see how orders come through and how your system responds, without real money at stake.

  • The goal of piloting is to uncover any practical issues now (for example, maybe you discover your shipping API wasn’t returning a needed field, or your tax calculation needs an update for the chat use case) and to get comfortable with the concept. It’s a learning opportunity for your team.

• Design for Flexibility: It’s possible that in a year or two, one of these standards will dominate or they might converge. Avoid hard-coding to one approach in a way that’s painful to change later. If you implement ACP now, do it cleanly – document the integration, and perhaps structure your code so that adding AP2 or another protocol later uses a similar pattern (e.g., through an abstraction layer or service class in your application). The merchants who handle omnichannel well have a unified layer to ingest orders from web, mobile, in-store, marketplaces, etc. – you might extend that concept to “agent orders.” In other words, treat the AI agent as another channel and build integration points such that you could plug in multiple agent platforms with minimal rework. For example, you might have an internal service for “CreateOrderFromAgent(agentPayload)” that currently only knows how to handle ACP payloads – but later you add logic for AP2 mandates or other formats. This way you’re ready no matter which protocol (or combination) wins.

• Monitor Results and User Sentiment: As you start getting AI-driven orders, watch them closely. What’s the average order value and conversion rate? Any fraud issues or strange patterns? Are customers happy with the experience (e.g., do they complain the AI ordered the wrong variant)? Early analytics will be gold. Instrument your analytics to identify agent-driven sessions versus human ones. This will help you refine the experience and decide where to invest more. If ACP orders are booming and AP2 is still quiet, you’ll prioritize accordingly (and vice versa). Share these insights internally – it’ll build support for further investment in AI commerce if you can show tangible revenue or learnings.

• Partner with Experts if Needed: Not every team has deep expertise in cutting-edge API integrations or AI. This is where partnering can help. For instance, Creatuity (that’s us!) is closely following these developments and helping merchants adapt. Whether it’s getting your Magento site ready for ACP, updating your infrastructure for AP2, or just auditing your store’s “AI readiness,” don’t hesitate to leverage experienced e-commerce solution partners. An investment now can save a lot of scrambling later when these technologies become mainstream.

Finally, keep an eye on the big picture: likely this standards race will shake out into either a dominant standard or a stable coexistence with clear use cases for each. We’ve seen similar situations in tech before (e.g., Blu-ray vs HD-DVD, or more analogously, different digital wallet standards). The winners tend to be those that balance security, convenience, and broad adoption. As a merchant, you want to be ready to ride whichever wave catches on – without over-committing to the wrong side.

Conclusion: Ready Your Store for the AI Commerce Era

Agent-driven payments are moving from hype to real implementation faster than many expected. In just a month, we went from “no solution” to multiple frameworks launched and even live transactions in the wild. This competition – Google vs. OpenAI vs. Visa and others – is actually a positive sign that trusted autonomous shopping is seen as the next frontier in commerce. The common theme is clear: marrying trust + convenience. Consumers will only embrace AI assistants buying things for them if it’s as seamless as magic and as safe as handing their credit card to a cashier. The standards we discussed are all trying to deliver that balance.

For merchants, the key takeaway is to start preparing now. You don’t have to implement everything immediately, but you should be AI-commerce-ready. That means excellent data hygiene, API capabilities, and a flexible mindset toward new channels. By taking steps to make your store “agent-friendly,” you ensure that your products can be present wherever your customers’ AI agents might go looking. Your ultimate North Star is simple: be there when an AI is shopping on behalf of your target customer. If their personal AI assistant is scouring the web for the best deal or auto-reordering supplies, you want your store in that consideration set – and you want the AI to be able to transact without hurdles.

The future of shopping might involve talking to an AI in your kitchen and having products show up at your door, with you barely lifting a finger. It’s a future where convenience is unparalleled. But behind the scenes, it will be enabled by the hard work and foresight of merchants and technologists building the trust fabric to support it. By acting now – even in small ways – you’re positioning your business to thrive in this coming wave of agentic commerce.

Next Steps: If you’re unsure where to begin or how these protocols could impact your e-commerce operations, consider reaching out for a consultation. At Creatuity, we specialize in helping mid-market merchants navigate emerging commerce technologies. We can assess your site’s readiness, assist with pilot integrations like ACP on Magento, and plan a roadmap tailored to your business. Book a consult with our team (see the “Book a Consultation” link in our header) – we’re here to help you chart a strategy so that when AI-driven shopping accelerates, your company is ahead of the curve, not scrambling to catch up.

In the end, the retailers who adapt early and thoughtfully will be the ones who can truly say: “No matter how you shop – through a browser, a chat, or an AI agent – we’re ready to serve you.”