How To Prepare for Agent-to-Agent Commerce

What Is Agent-to-Agent Commerce?

AI storefronts provide both the front door for human shoppers and the back door that opens the way for agent-to-agent commerce. In agentic commerce, the buyers and sellers aren’t people—they act on behalf of them, working with set boundaries and preferences to autonomously complete purchases. 
Soon, a shopper’s AI agent will deeply understand their needs, preferences, and intent, while a retailer’s AI agent will manage the product data, inventory, and infrastructure to fulfill the purchase. Together, these agents connect demand and supply, instantly completing the shopping and purchasing path independently.

A shopper will no longer need to take on the manual burden to browse, shop, and buy. Retailers will no longer need to rely on static selling experiences and UI that lead to low conversion rates. Agentic commerce marks the end of generic storefronts and funnels, giving way to adaptive, AI-powered experiences that truly convert.

An Example Of How Agent-To-Agent Commerce Works:

Agent-to-agent commerce shifts the competition away from capturing human attention to being trusted and selected by AI agents.

As the technology advances, this process could even look like an AI agent seeing a wedding invite on your calendar, asking if you need help getting ready for it—from what to wear to purchasing a gift, coordinating your flights and hotel—and taking care of it all. We’re not quite there yet, but we’re not far.

How Do AI Shopping Agents Interact With Each Other And The Shopper?

Agent-to-agent commerce works by connecting richly structured data, secure transaction APIs, and orchestration layers that allow AI agents to “talk” directly to storefronts based on what a customer has sent them to shop for. 

With every product attribute (size, color, price, availability, compatibility, materials, reviews, etc.) served in a standardized format (like JSON, XML, etc.), AI agents can query, compare, and qualify products without human intervention.

AI shopping assistants or “agents” could come in various forms: 

Generative AI Platform Shopping Companions
AI assistants in platforms like Perplexity, Gemini, or ChatGPT pass queries to and pull matches from AI storefronts. To show up in these searches, retailers will equip their agents with all the product and selling data needed, while also optimizing their content and products to show up in AI platforms. Researching and purchasing is handled between a generative AI assistant and the AI storefront. 

Voice Assistants and Hands-Free Purchases
Assistants across smart devices (like Alexa) that offer voice-driven AI shopping. A shopper says, “order me the best 6-cup coffee machine under $50” and the assistant is able to process the command without the customer ever opening a device.

Across The Same AI Storefront
Within a retailer’s own storefront, there can be multi-agent systems that all layer up to the main assistant that a customer interacts with. So for a customer trying to plan a trip, one agent covers flights, another hotels, to make one holistic itinerary.


How Retailers Need to Prepare for Agent-to-Agent Commerce

To support agentic commerce, your e-commerce can’t only be optimized for clicks and front-end UX—it also must be search-optimized for generative AI platforms, machine-readable, structured, and agent-ready. Here’s how:

• Structure product data — Agents rely on clean, consistent product feeds with attributes like size, material, compatibility, and availability. Make sure product data is richly structured, enriched, and always accurate and available in real-time. 
• Enable secure transactions — APIs or MCPs (multi-capability protocols) must give agents a clear endpoint to authenticate agents, queries, retrieve data, and transact safely while also protecting retailers’ and customers’ data.
• Move to an AI storefront — Storefronts should be conversational, adaptive, and ready to serve agents the same way they serve human shoppers: fast, personalized, and adaptive. Continuing to rely on static filters, “smart search” and chatbots will negatively impact your traffic, conversion, and LTV.
• Start training your AI shopping assistant — The LLMs that power current chatbots work on prediction curves. AI shopping assistants will learn by actual experience. The more and the sooner they can interact with real customers, the better they can put effective sales strategies and real-time decision-making in practice. You can do this with the iAdvize Copilot™ in a matter of days. 
• Track new traffic types — Understand your new site traffic breakdowns across traditional search, social media, AI referrals, and agent-to-agent transactions to ensure you’re providing a smooth and consistent experience across all of them and adapt your marketing strategies to them. 
• Incorporate agentic SEO practices — On top of classic SEO best practices, get great at answering more direct, specific questions. Answer the top 50-100 questions people have about your product, use richly structured data, create glossaries and lots of FAQs.
  

The Next Era Belongs to Agent-to-Agent Commerce

While AI storefronts are retailers’ front doors for human customers, the real shift will come through the back door, when AI agents transact directly with one another on behalf of a customer.

The question is not if AI agents will do the shopping, it’s whether those agents will buy from you or bypass you entirely. Retailers who act now by structuring data, securing APIs, and launching AI storefronts will capture and delight customers by fixing the broken “browse and hope” shopping journey—ultimately helping retailers land their products in the right hands and enabling customers to truly enjoy their purchase with less friction than ever before.