Agentic Commerce

Agentic commerce is shopping in which an AI assistant discovers, compares and increasingly buys products on a shopper's behalf, across ChatGPT, Google AI Mode, Perplexity and other surfaces.

Last updated: 2026-10-03

What Is Agentic Commerce?

Agentic commerce is the model in which an AI assistant handles part or all of the purchase journey. For the complete breakdown, see our guide to agentic commerce. Instead of a person searching Google, opening product pages and checking out by hand, the assistant reads product catalogs, compares options across retailers and, where the platform supports it, completes the transaction through protocols like ACP, UCP, and MCP.

The term covers AI shopping across the major platforms: ChatGPT Shopping, Google AI Mode, Perplexity, Claude and a growing set of specialized agents. Morgan Stanley projects the AI-powered shopping market growing from 3.36 billion dollars to 28.54 billion by 2033 (Morgan Stanley, 2026).

Where traditional ecommerce competes for human attention through design and marketing, agentic commerce runs on data. An assistant evaluates products on their attributes, not their photography. Retailers whose product information is complete and accurate get recommended. For the retailer-facing primer, see Paz.ai's retailer's guide to agentic commerce and the launch-moment analysis agentic commerce just left the building.

How Agentic Commerce Works

Discovery, evaluation, recommendation and, where supported, transaction.

The agentic commerce flow has four stages:

Discovery. A shopper asks in plain language ("find me waterproof hiking boots under 200 dollars"). The assistant works out the intent and searches product catalogs, feeds and indexed web pages.

Evaluation. It compares products on the attributes that matter to the question: material, weight, waterproof rating, price, reviews, availability, shipping. Complete, accurate data gives it more to work with.

Recommendation. It presents a shortlist. Many of these conversations end without a click to any retailer, so the recommendation is the moment of influence.

Transaction. Depending on platform and protocol, the assistant either completes checkout itself (UCP in Google AI Mode) or sends the shopper to the retailer's site (ChatGPT's current model after OpenAI pulled back from native checkout in March 2026).

Key Protocols Powering Agentic Commerce

Three protocols underpin it: ACP (OpenAI and Stripe), UCP (Google and Shopify) and MCP (Linux Foundation).

Standard protocols define how assistants talk to merchant systems:

Agentic Commerce Protocol (ACP) was built by OpenAI with Stripe for ChatGPT Shopping. It covers discovery through checkout with Stripe as the payment rail. OpenAI moved from native checkout to a referral model in March 2026.

Universal Commerce Protocol (UCP) is Google's standard, built with Shopify. It powers Google AI Mode shopping and has the broadest merchant adoption, with payment partners including Nexi and Splitit.

Model Context Protocol (MCP) started at Anthropic and is now governed by the Linux Foundation. It is the general-purpose connection an assistant uses to read live data, increasingly including commerce systems.

Market Size and Adoption Data

Shopify reports 15x growth in AI-originated orders. Forrester finds a third of Gen Z shoppers already use AI agents for shopping.

Adoption is moving quickly across consumer segments and platforms:

  • Market size: 3.36 billion dollars in 2024, projected to reach 28.54 billion by 2033 (Morgan Stanley, 2026)
  • Order growth: Shopify reports a 15x year-over-year increase in AI-originated orders (Shopify, 2026)
  • Consumer adoption: 23 percent of Gen X and 35 percent of Gen Z have used AI agents for shopping tasks (Forrester, 2026)
  • Referral traffic: AI referral traffic to US retailers up 393 percent year over year in Q1 2026, converting better than other traffic (Adobe Analytics, April 2026)
  • Platform scale: ChatGPT reports 800 million or more weekly active users, and Google AI Mode is part of Google Search

What Retailers Need to Do

Complete the product information, keep feeds and structured data accurate, and watch how your products appear in AI answers.

The work for a retailer is mostly about product information:

Complete the product data. The attributes relevant to each category: material, dimensions, care, compatibility, certifications, use case. This is what assistants filter on.

Keep feeds accurate. Merchant Center feeds power Google AI Mode. Use product_detail attributes beyond the standard fields and keep price and stock current.

Add structured data. JSON-LD with additionalProperty, complete aggregateRating, offers with shipping details and MerchantReturnPolicy, matching what the feed says.

Watch AI visibility. Ask ChatGPT, Google AI Mode and Perplexity the questions your customers ask, on a schedule, and track whether your products appear.

The discipline around this is called Agentic Commerce Optimization. Paz does this work for ecommerce teams: a Paz expert finds the gaps that matter for your products, prepares source-based fixes within agreed guidelines, and tracks appearances over time. See how it works.

FAQ

What is agentic commerce?+
Agentic commerce is shopping in which an AI assistant discovers, compares and increasingly buys products on a shopper's behalf. Instead of browsing websites, the shopper asks, and the assistant reads structured product data, evaluates options and, where supported, completes the purchase through protocols like ACP, UCP and MCP.
How big is the agentic commerce market?+
Morgan Stanley projects the AI-powered shopping market growing from 3.36 billion dollars in 2024 to 28.54 billion by 2033. Shopify reports a 15x year-over-year increase in AI-originated orders.
What platforms support agentic commerce?+
ChatGPT Shopping, Google AI Mode, Perplexity Shopping, Claude and Amazon Buy for Me. Each connects to merchant catalogs in its own way, and all of them read the same product information.
How do retailers prepare for agentic commerce?+
Complete the product attributes that matter in each category, keep feeds and JSON-LD accurate, and track how products appear across the assistants your customers use. Most retailers do this in-house, through an agency, or as a handled service like Paz.
What is the difference between agentic commerce and traditional ecommerce?+
Traditional ecommerce relies on people browsing, clicking and checking out themselves. In agentic commerce an assistant does the browsing and comparing, and sometimes the buying, from structured product data rather than from design or marketing. The shopper still decides, but from a shortlist the assistant built.

Related terms

Agentic Commerce Protocol (ACP): What It Is and How It Works

The Agentic Commerce Protocol (ACP) is an open standard, maintained by OpenAI and Stripe, that defines how a shopper, their AI agent, and a merchant complete a purchase while the merchant stays the system of record.

Universal Commerce Protocol (UCP)

UCP is an open standard by Google and Shopify that enables AI agents to handle the full commerce journey from discovery to post-purchase.

Model Context Protocol (MCP)

MCP is an open standard, created by Anthropic and now governed by the Linux Foundation, that gives AI agents one common way to connect to external data sources and tools in real time.

AI Shopping Agent: What It Is and How It Works

An AI shopping agent is software that searches, compares, and can purchase products on a consumer's behalf through natural language conversation, with degrees of autonomy that range from research to completed checkout.

Zero-Click Buying

Zero-click buying is the idea that an AI agent handles product discovery, comparison and selection for a shopper, so the steps between intent and purchase shrink to a confirmation or nothing at all.

Agentic Storefront

An agentic storefront is a merchant's presence inside AI shopping assistants: the product data, checkout path and brand signals that appear when ChatGPT, Perplexity or Google AI Mode recommend their products.

How AI-ready are your products?

Check one product page for the information gaps that keep it out of AI answers and search results. If you want the fixes handled, Paz experts do that work for ecommerce teams.

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