Traditional ecommerce assumes that a human searches, opens product pages, compares options, adds an item to cart and enters payment details. Agentic commerce can compress that journey because an AI agent may perform several of those steps for the buyer.
1. Intent
The process begins with a goal rather than a keyword: find a compatible product, stay within a budget, deliver by a date or satisfy a business requirement. The quality of the transaction depends on whether the merchant exposes enough reliable information for the agent to interpret that goal.
2. Discovery and qualification
The agent identifies products and evaluates attributes, variants, price, availability, merchant policies and other constraints. This connects Agentic Payments directly to Machine Experience and Machine Interface: payment cannot rescue a product that was misunderstood upstream.
3. Cart and checkout
Once a product is selected, the machine needs a supported interface for cart creation and checkout. Open commerce protocols and platform-native checkout capabilities can reduce the need for brittle browser automation.
4. Authorization
The crucial boundary is permission. An agent needs to know what it may spend, for whom, using which payment method and under what conditions. High-value or unusual purchases can still require explicit human confirmation.
5. Payment and order
The payment rail may be Shop Pay, a card network, wallet, bank-based rail such as UPI, or another supported provider. The result must reconcile back to a valid merchant order.
Explore the architecture in What Are Agentic Payments? and the Shopify-specific layer in How Shopify Agentic Payments Work.
What merchants should optimize
The future checkout funnel is not only visual CRO. Merchants also need machine-readable product truth, predictable interfaces, explicit policies and trustworthy payment paths. Codified Commerce treats this as an end-to-end Agentic Commerce problem: make the store understandable, actionable and safely transactional.
