Agentic Commerce: The Next Shift in Online Retail

How do customers find a product today?

Just a few years ago, the answer was simple: Google.

A customer would search for something like "women's running shoes size 39", open several online shops, compare products and prices, and then decide on a provider.

Today, product search increasingly begins differently.

Instead of searching through ten shops themselves, the customer can ask ChatGPT, Gemini or another AI assistant:

"I'm looking for women's running shoes, size 39, mainly for asphalt, maximum 150 euros. Which models fit?"

The AI takes over part of the research, structures information and suggests suitable products.

But this is precisely where the next stage of development in e-commerce already begins.

From Product Search to AI Shopping Agent

So far, AI has mainly helped find and compare products.

Agentic Commerce goes a step further.

An AI agent should not just read information about products, but be able to communicate directly with online shops.

This means, for example:

"Find suitable running shoes in size 39 up to 150 euros and show me only models that are currently available."

This means the AI no longer has to try to piece together information from individual web pages. The shop can provide product data in structured form and answer specific queries.

This is how the path to purchase is changing:

Before: Google → Search result → Online shop → Product search → Product → Shopping cart

Today: AI assistant → Research → Product recommendation → Online shop → Purchase

Agentic Commerce: Customer request → AI shopping agent → Product search across connected shops → Comparison → Product selection → Shopping cart

Why Online Retailers Should Pay Attention to This

This creates a new access point to retailers' own product range.

Until now, a product mainly had to reach two target groups: the customer and the search engine.

Now a third is added: the AI agent.

A human can click through categories, look at product images and interpret text.

An AI agent, by contrast, needs information that is as clear and structured as possible:

• What kind of product is this?
• What variants are available?
• What size is available?
• What is the current price?
• Is the item in stock?
• What features does it have?
• What alternatives are available?

The better this information is technically accessible, the better an AI can understand the product range.

How Is Online Shopping Changing?

1. Search Commerce Customer → Google → Search results → Online shop → Product → Purchase

2. AI-assisted Commerce Customer → ChatGPT / Gemini / AI Search → Research & comparison → Product recommendations → Online shop → Purchase

3. Agentic Commerce Customer describes their need → AI shopping agent → communicates with various shops → checks products, variants, prices & availability → selects suitable offers → prepares the purchase

The decisive difference: AI no longer just leads to the shop. It can communicate directly with the shop.

How Can an AI Agent Talk to a Magento Shop?

New technical standards and protocols are currently emerging for this.

One of them is the Model Context Protocol (MCP).

Put simply, MCP can be thought of as a standardised connection between an AI and external systems.

A Magento shop can use it to provide certain information and functions.

The AI agent could, for example, ask:

"Which women's running shoes in size 39 under 150 euros are currently available?"

The shop returns a structured answer.

This means the AI doesn't have to try to read a web page like a human.

It receives the information it needs directly from the commerce system.

In addition, other standards such as UCP and WebMCP are being developed, which also aim to make commerce systems accessible to AI agents.

Does This Mean the End of Google and SEO?

No.

Customers will continue to use Google, visit shops directly, open newsletters, use social media and carry out classic product searches.

Rather, an additional access point to the online shop is emerging.

That's why classic SEO remains important. At the same time, structured product data and the technical readability of a shop for AI systems are gaining importance.

In addition to SEO – How does Google find my products?, the question now also arises: AI Commerce – How does an AI find and understand my products?

Magento Provides a Good Foundation for This

Magento already manages a great deal of information in structured form: product names, categories, attributes, variants, prices, stock levels and other product information.

This data doesn't need to be maintained separately for every AI.

The technical task consists instead of making selected information and functions accessible to AI agents in a controlled way.

Magento remains the leading commerce system in this context.

The retailer decides which data and functions are made available.

Does an Online Shop Already Need This Today?

Agentic Commerce is still at an early stage of development. Standards, platforms and possibilities are currently changing very quickly.

That's why it's not about completely rebuilding an existing shop for AI today.

It makes more sense to check:

• Is our product data cleanly structured?
• Can an AI clearly understand our products?
• What technical interfaces does our shop already have?
• And how could an AI agent access our product range in a controlled way in the future?

Because the interesting question for online retailers is no longer just: "How well does Google find my shop?"

But increasingly also: "Can an AI shopping agent find, understand and offer my products to its users?"

Is Your Online Shop Ready for AI Commerce?

Whether ChatGPT, AI Search or future shopping agents: what matters is whether your product data and your shop can be technically understood and used by AI systems.

With our AI Commerce Readiness Check, we review the key technical prerequisites of your online shop and show you exactly what already works and where there is still room for optimisation.

€499 plus VAT — Start the AI Commerce Readiness Check