This is part 3 of our Agentic Protocol for Ecommerce series. 

Read Part 1: The Universal Commerce Protocol (UCP): What It Is and Why It Matters for Ecommerce

Read Part 2: The Model Context Protocol (MCP): The Agentic AI “USB-C Port” for Ecommerce

AI agents are rapidly changing how people interface with the tools and websites they use every day, and forward-thinking ecommerce merchants are beginning to leverage these bots to get more done and increase sales. 

These autonomous AI agents can handle tasks such as purchasing on behalf of users, making product recommendations, updating inventory, and handling customer inquiries, but we have one small issue: all these bots can’t natively talk to each other, limiting the usefulness of AI agents in ecommerce.

For agentic commerce to really take off, we need to ensure that multiple AI agents (for shopping, inventory, marketing, support, etc.) can communicate across systems. Today’s tools are siloed. We need a common framework so agents from different platforms can talk to each other.

Thankfully, protocols are emerging to fill these gaps and ensure that AI agents can communicate effectively with one another to unlock the full potential of agentic work. In this blog, we’ll break down the Agent2Agent (A2A) Protocol, an open standard developed by Google that enables agents from across the web to work together using a common language. 

What is the A2A Protocol?

The Agent2Agent Protocol was originally developed by Google in April 2025 and later donated to the Linux Foundation to enable AI agents built on different platforms to exchange information, coordinate actions, and securely delegate subtasks within complex workflows. 

Instead of a human telling a single chatbot what to do, A2A enables many specialized AI helpers to collaborate. For example, an agent built for shopping might team up with an inventory agent and a pricing agent without any one agent handling everything. This mirrors real teams: specialists coordinate to solve complex problems. 

Think of A2A as a universal translator and coordination framework, letting agents discover one another, exchange structured messages, and complete complex workflows that one agent couldn’t tackle on its own. 

How A2A Enables AI Agent Collaboration

Agents are independent, autonomous problem solvers. Anyone could build an AI agent capable of accessing specific information and completing specific tasks. This agent can work independently within its environment, but needs the help of A2A if the creator of the agent requires it to interface with a different agent, built by someone else on a different framework. 

With A2A, agents can find each other. A2A lets one agent publish its capabilities (for example, “I handle order processing”), and others can search for it. In ecommerce, a customer service agent might connect with a supply chain agent, or a loyalty agent might connect with a marketing agent to align offers.

Agents can send structured messages to share data. For example, an AI-powered inventory agent could tell a marketing agent that stock is low, or a product agent could send product details to a shopping agent. The protocol specifies message formats so everything is clear and consistent, even if agents come from different vendors.

These agents can negotiate and delegate subtasks. If a complex request comes in, one agent can break it into pieces, handing off tasks to agents better suited to complete specific actions. 

Ecommerce Workflows Powered by A2A

Leveraging multi-agent workflows in ecommerce can unlock all kinds of capabilities. Here are a few examples to get you started with A2A-enabled AI tools:

1. Inventory Management: AI can keep stock levels accurate. For example, an inventory agent in your store could detect when an item is low on stock and, via A2A, notify a restock agent or even place an order automatically.

2. Marketing Coordination: Marketing campaigns often depend on other systems. With A2A, a marketing agent could coordinate with a pricing agent and an inventory agent. For example, if data shows excess inventory of an item, an agent might automatically create a targeted discount promotion. It could identify which customers might want the item, generate marketing content, launch a sale, and update product listings, all through API calls across platforms.

3. Cross-Platform Automation: Because A2A is platform-agnostic, it can facilitate a wide range of cross-platform agentic workflows. Whether you use Shopify, Adobe Commerce (Magento), or a headless system, agents can interoperate and perform tasks together. The merchant doesn’t have to “pick sides” as A2A is an open standard everyone can adopt.

For developers, Google offers an Agent Development Kit for the A2A Protocol to build your own multi-agent systems capable of completing complex tasks. It’s designed for flexibility, allowing users to integrate various large language models (LLMs) like Gemini or Claude into their agents.

There are also a ton of pre-built tools available for users to leverage with ADK agents, such as Google Search, BigQuery Agent Analytics, PayPal, and GitHub (or you could build your own). 

A2A and the Agentic Commerce Ecosystem 

A2A fits into a new ecosystem of AI-driven commerce standards. The Universal Commerce Protocol (UCP) is a companion standard that helps agents read and write ecommerce data. The Model Context Protocol (MCP) connects agents to external systems. The Agent Payments Protocol (AP2) can also be leveraged to securely handle agentic payments.

A2A is the glue between agents. In other words, MCP and UCP handle data and transactions while A2A handles agent-to-agent messaging, and AP2 keeps payments secure. 

Think of it this way: A2A enables autonomous agents to partner and collaborate on tasks, while MCP focuses more on agents using capabilities. A merchant using all of these protocols in tandem can unlock a level of AI-powered ecommerce automation and personalization on a scale unheard of otherwise. 

By orchestrating multiple agents, businesses can automate end-to-end processes. Routine tasks such as inventory restocks, campaign launches, and data syncs can be automated without human intervention. Google notes that agent collaboration multiplies productivity and lowers costs. Instead of manual monitoring, agents keep workflows moving 24/7. 

Additionally, with A2A, companies can deploy specialized agents as needed. If one agent fails, others can compensate or retry, thanks to the protocol’s support for long-running tasks, problem-solving, and retries. The system is not reliant on one monolithic bot.

As more brands and customers begin experimenting with AI agents in their day-to-day, these protocols are quickly becoming the backbone of modern ecommerce. As a merchant, it’s important to ensure you are set up to be discoverable by these tools so your products can be found by users shopping via agentic commerce/LLMs. 

Conclusion

If you’re already exploring AI automation, now’s the time to prepare your business for agentic commerce. Protocols like A2A are quickly becoming essential for staying competitive, enabling faster decisions and 24/7 autonomous operations. 

If you want help making your ecommerce stack A2A-ready, we at Blue Badger can guide you through the integration process, keep it secure, and ensure your AI initiatives deliver real value. Contact us today to get started with agentic commerce.