The Rise of Agentic AI Checkout: Preparing Your eCommerce Brand for the Next Wave of Shopping Automation

The Rise of Agentic AI Checkout

AI checkout agents, such as the ChatGPT Agent, are emerging as the next shiny toy in ecommerce convenience. Unlike traditional “add to cart” and manual checkout flows, these AI agents act on behalf of the shopper: navigating sites, comparing products, and completing purchases without requiring the user to navigate the typical checkout process (they can do a whole lot more than buy you things, but for this article, we’ll focus on their role in eCommerce shopping).

This agentic tech goes beyond ChatGPT and Gemini’s AI Mode, companies like Visa and Mastercard recently announced plans to invest in these applications.

For consumers, the opportunity is clear: frictionless shopping. Whether it’s reordering a skincare product or grabbing a last-minute gift, AI checkout agents can research, recommend a product, and purchase it for you.

For ecommerce brands, the shift brings opportunity. Online stores that are technically ready for AI agents stand to gain first-mover advantages amongst LLM enjoyers. Those that aren’t prepared risk brand visibility amongst a growing class of automated buyers. The time to evaluate readiness, test compatibility, and align your store with this new wave of commerce is now.

Brand Fit: Should Your Brand Prioritize AI Checkout?

Before we jump in, those with other day to day priorities may be asking: how much opportunity is there with agentic checkout? Will my audience even care about this? These are the right questions to ask, however it’s my view that agentic checkout will benefit almost any ecommerce store, even if some product categories are better positioned. Here’s who I believe will see agentic checkouts first:

Lower price point or repeat-purchase products—think consumables, household items, supplements, even certain types of apparel (flip flops come to mind) are prime candidates. These purchases often involve little decision-making once a customer has asked a couple of questions or have a preferred brand, making them perfect for AI agent.

High-consideration or “retail therapy” purchases, on the other hand, may be less suited to agent-driven buying. Products like luxury fashion, fine jewelry, electronics, or more visual products, often involve emotional engagement, in-person try-ons, or extended comparison shopping. In these cases, a fully automated checkout may bypass the ‘joy of the customer experience’.

The best approach is to analyze your target customer’s buying behavior and ask yourself:

What’s your price point?
How often do they purchase from you?
Do they tend to repurchase known items or explore new options?
How much ‘education’ does your product require?

By aligning AI checkout readiness with customer behavior, brands can focus their investment where it’s most likely to deliver measurable ROI—while keeping the human touch where it matters most.

Initial Barriers to Adoption

The potential for Agentic AI checkout is exciting, but not without roadblocks, both intentional and unintentional, that can prevent AI agents from completing purchases. You may remember these recent news stories:

Shopify & robots.txt

Just four+ weeks ago, Shopify updated its default robots.txt file to block AI checkout agents from crawling and interacting with their stores. This has since been reverted, potentially sending a message that reflects broader industry caution (see Cloudflare’s similar move) around bot-driven transactions.

John Mueller on Agent Barriers

SEO’s read the advice from John Mueller, but in case you haven’t, here are common access barriers to avoid on your site:

CAPTCHA walls – For example, a ChatGPT-powered agent was stopped mid-purchase due to a CAPTCHA verification.
Cloudflare Turnstile – A CAPTCHA alternative that can similarly block automated agents.
Maintenance pages – AI agents hitting a temporary “site under maintenance” page will fail the purchase attempt.
Bot defense systems – Advanced security tools designed to detect and stop non-human traffic, which can include legitimate AI checkout bots.

Early Best Practices for AI Checkout

Before an AI checkout agent can seamlessly complete a purchase on your site, it needs to “read” your store’s structure and data. The following is collected wisdom, or what we know so far, to ensure agents can fully understand your storefront and products.

1. Review Your JavaScript and Frontend Frameworks

SEOs have noted LLMs can have trouble with Javascript heavy storefronts. Heavy or unconventional JavaScript frameworks can make it difficult for them to interpret product details, prices, or checkout flows. Audit your site for compatibility and ensure that essential product and checkout information isn’t hidden behind scripts that agents can’t parse.

To test this, ask your SEO team to run a Screaming Frog crawl without JavaScript and identify missing information or even URLs.

2. Fully Optimize Structured Data

Structured data is vital for eCommerce. Schema.org supports how AI agents, and search engines, understand what’s on your pages through spelling out key pieces of information about your products. While each site and product is different, every product page should clearly include the following basic markup:

Name
Description
Images
Price
Reviews (both aggregate review totals and individual reviews)
Shipping information like free shipping thresholds

For stores with product variations at unique URLs, such as different sizes or colors, use the newer ProductGroup schema instead of relying solely on individual Product schema. ProductGroup helps search engines and AI recognize related SKUs and guide customers directly to the right variation on SERPs and chatbots.

3. Keep Google Merchant Center Synced and AccurateAn up-to-date Google Merchant Center feed increases the likelihood that your products will surface correctly in AI-driven shopping flows, especially Google’s AI Mode.

If you’re on Shopify, you can use its automated feed sync to keep Merchant Center aligned without manual updates. If you do choose the more manual route, ensure all product titles, descriptions, prices, and availability matches what’s on your site.

By ensuring these technical fundamentals are in place, you’re making it easier for AI checkout agents to understand your products, process orders accurately, and deliver a frictionless experience to your customers.

4. Measuring and Monitoring Performance is Key

Enabling AI checkout is only the first step—tracking its effectiveness is vital. At BMG360, we use a combination of tools to track performance, but setting up a simple Explore report within GA4 to track traffic by LLM source is a great way to start:

Simply drop in this regex filter into your Explore report and start tracking LLM performance:

An eCommerce SEO’s Thoughts on Agentic AI

Regardless of your industry, it will take time for meaningful adoption of agentic checkout. Outside of LLM best practices/GEO and ensuring your site works with AI agents, I wanted to talk about my thoughts for the future:

I am eyeing tools like Gemini AI Mode’s “try it on” feature for apparel/fashion clients and would be interested in testing email campaigns requesting a fashion brand’s customer base to enable the feature and try it out. In theory, this sounds like a great way to ask customers to envision that shirt, dress, shoe, whatever on themselves, possibly encouraging additional sales.
Similar to the “Try it on” feature discussed above, I envision CRO teams foaming at the mouth to try out new, AI powered tools right on PDPs. Tools like this come to mind.
I would seriously think about enabling Google Pay on your brand storefront. If Gemini’s agentic shopping experience takes off, you’re going to want to play along and support Google’s payment system.
If you sell on Amazon, I would monitor sales. Due to Amazon’s nearly unbeatable shipping speed, if all else is equal (price, inventory, product availability, etc.), I have a gut feeling agents will default the purchase through Amazon so the customer can get it sooner. Confirm everywhere you sell your products online and you might be able to anticipate/ explain an increase in Amazon sales.
At this stage, adopting the proposed LLMs.txt standard, a file that signals how large language models can interact with your site, is still optional in my opinion. It is worth considering, but not mandatory for most brands as robots.txt is good enough for now.

Conclusion

It’s impossible to predict what’s to come, but one thing’s certain: start measuring this stuff! It’s the only way to know if your customers use it.

The brands that will win in this space aren’t necessarily the biggest, but the ones that prepare early: ensuring technical readiness, removing access barriers, and aligning AI shopping flows with their customers’ buying habits. Treat this moment as a ‘test and learn’ phase. Every adjustment you make now positions your store to thrive as these agents become a growing part of ecommerce. Agentic purchases start as a small percentage of online sales, but it may grow, and you won’t want to miss out.

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