An "AI-ready" store is one that has an complete and up-to-date product data (feed + Schema.org + API with pricing and availability) and a purchasing process ready for traffic from external agents. If these foundations are incomplete, ChatGPT simply Cannot correctly identify and recommend your products, no matter how good your marketing is.

What does it mean for a store to be "AI-ready"?

In practice, "AI-ready" means four things: you have an up-to-date product feed, correct Schema.org structured data, an API with real-time pricing and availability, and a shopping process ready to accept external traffic. This has nothing to do with chatbots, customer service or AI recommendations. It's the foundation of product visibility in the shopping conversation with ChatGPT.

AI-ready store:

• has structured product data in a format that language models can understand,
• supports fast and automated checkout,
• Can accept traffic and orders from external agents,
• presents the offering in a way that AI can recognize and interpret.

In other words: ChatGPT doesn't "see" your store like a human does. It doesn't look at the page, it just gets data from feeds, APIs and structural tags. If these elements are incomplete or inconsistent, you don't exist for the system. Being AI-ready doesn't require ACP or full checkout - discovery, or the ability to find a product in a conversation, also requires proper data preparation.

(If you don't already know how the ChatGPT sales process itself works - from conversation to purchase - see our article: Selling through ChatGPT: how it works, for whom it makes sense, and how to implement it step by step.)

Why does an AI-readiness audit make sense now?

In 2025, OpenAI, Microsoft and Shopify began piloting conversational commerce in selected countries. ChatGPT users can already browse products, compare prices and even make payments via Stripe without leaving the conversation.

It's a breakthrough moment because it doesn't require the customer to type in the store's address or visit the site. If your store is not present in the feed ecosystem or does not have the correct structural data, AI will simply skip it.

A readiness audit thus helps answer the question: Does ChatGPT even know I exist?

Four pillars of store readiness to sell through ChatGPT

Before you start integrating or investing in new technologies, it's worth understanding that a store's readiness to work with AI agents is not a single project, but a set of competencies.
Each pillar has a different role: data tells AI, what you sell, UX shows how easy it is to buy, technical integrations allow execute the transaction, and content makes the agent understands your offer and context.

These are the four areas that form a solid foundation for conversational trading. If one of them fails, the whole process falls apart.

1. data and feeds

This is the most important part of the audit - if the feed is weak, no other area (checkout, API, content) will make up for the visibility. ChatGPT needs data about your products that it can understand and relate to the context of the conversation. Therefore, the product feed and structured data must be complete, up-to-date and conform to Schema.org's format (Product, Offer, Review).

The audit analyzes, among other things:

• Availability and correctness of the feed (XML, JSON, CSV),
• Uniqueness of titles and descriptions,
• The presence of data on price, availability, reviews, photos,
• Quality of metadata (e.g., brand, material, application).

It is this data that allows the agent to understand that "eco-friendly cork yoga mat" from your store is the answer to the user's question about a gift for a person who practices yoga.

Most common mistakes:

• outdated feed / manual updates,
• No price or availability (no Offer → no indexing),
• Repetitive descriptions like "high quality product."

(You can read more about feed preparation and structured data in our article: Store visibility in ChatGPT: how product discovery works and how to appear there.)

2. UX and checkout

The AI agent won't click on a banner, wait for the page to load, or manually enter card data. Therefore, the shopping process must be short, simple and compatible with payment integrations (Stripe, PayPal, Shopify Payments).

During the audit, it is checked:

• how many steps separate the customer from the purchase
• Whether redirection from an external agent can be handled,
• Whether a shipping and returns policy is available in the metadata,
• Whether the payment system has an open API or Instant Checkout support.

Examples of ChatGPT blocking errors:

• The link to the shopping cart opens a 404 page,
• The shopping cart requires acceptance of a popup that the AI agent can't close.

ChatGPT sends a direct link to a shopping cart or a specific product. If your UX doesn't support this flow, you're missing out on conversion opportunities.

(For more on preparing your store for chat shopping, see the text: Agentic Commerce Protocol (ACP): how to prepare your store for chat shopping.)

3 Integrations and APIs

An AI-ready store must "talk" to other systems. This means the availability of APIs or webhooks that allow the agent to retrieve information about price, inventory or shipping costs.

In practice, this means audit questions such as:

• Does your CMS (Shopify, WooCommerce, PrestaShop) have a public API or access token?
• Is the product data updated automatically?
• Can your CRM or ERP system sync with your product feed?

Without an API for real-time price and availability, there is virtually no chance of visibility in ChatGPT's shopping queries.

4. content and language

AI doesn't understand marketing jargon - it needs to get specific. If you have "a high-end product from a leading brand with innovative technology" in your description, AI has no idea what you mean. It needs simple, descriptive sentences that define, what it is, for whom, why And what parameters it has.

In a language audit, it works:

• Whether the descriptions are specific and understandable,
• Whether titles provide context (e.g., "350 ml steel thermal mug" instead of "premium mug"),
• Whether the content contains natural words that people type into the questions,
• Whether the photos have appropriate alt tags.

What does an AI-readiness audit look like in practice?

Based on data from feeds, site, SEO tools and technical integrations, a report is created that shows where you are today and what you need to improve.

The most common audit includes:

1. Technical module - Feed analysis, schema.org, APIs, speed and data availability.
2. Operations module - Integrations with CRM, ERP, payment systems, marketing automation.
3. Language module - Analysis of descriptions, meta data, product labels and communications.
4. Strategic module - Assessing whether the store has a plan to enter agentic commerce, including performance measures.

The report concludes with a rating on a scale of 0-100 in each area and recommendations for action for 3 stages:

• Quick wins (e.g., adding structured data, improving feed),
• Medium-term (BMC integrations, description automation),
• Long-term (ACP implementation and full integration with ChatGPT Merchants).

How do you independently check if your store is AI-ready?

You don't need an external audit right away to figure out where you are.
Answer these questions for yourself:

• Do you have an up-to-date product feed in XML or JSON format?
• Does your site have Product/Offer structured data?
• Are the product descriptions unique, specific and natural?
• Does the buying process work in less than three steps?
• Do you have an integration with Bing Merchant Center or Shopify?
• Does your API allow you to retrieve product data?
• Is the return and delivery policy public and tagged with metadata?
• Does the payment system support Stripe or a similar solution?

If you answered "yes" to most of these questions, you're closer than you think.

What an AI-ready audit report looks like

The report is not just a technical list of errors. It's a guide to show where an investment in data improvement will make a real difference.

Includes:

• Overall readiness score (AI Readiness Score),
• Description of the current state (what works, what doesn't),
• Recommendations for action With priorities,
• Implementation map - A step plan broken down into weeks or sprints.
• Automation of feed updates (no manual changes).

Why you should do an audit now

The implementation of ChatGPT Merchants and ACP in Poland is only a matter of time. When the system opens to new markets, the first stores with a ready feed and data will appear in the results automatically.

Audit performed today:

• gives you an advantage at the start,
• allows you to prepare data before launching purchasing agents,
• Allows you to test your feed in Bing Merchant Center,
• saves time when ChatGPT Shopping officially enters Europe.

ChatGPT's sales readiness audit -. summary

Chat sales start with data.
When products are described clearly, have consistent attributes and live in current feeds, an agent can find them without prompting. If this is missing, even a great campaign won't cover the chaos.

An AI-readiness audit is the first glimpse of a store through the eyes of a model. It checks what is visible, what is not understood, and what is silent. It also teaches you to speak the language of machines: precise attributes, consistent naming, real-time availability. So much and so much. From this point on, the ads really have something to target.