TL;DR — Key Takeaways
- Google’s A2A protocol is moving under the Agentic AI Foundation as momentum builds around standards for agent-to-agent interoperability.
- A2A lets AI agents discover capabilities, delegate tasks and communicate across different frameworks and vendors without bespoke integrations.
- A2A 1.0 adds features including multitenancy, protocol negotiation and signed agent cards designed to strengthen enterprise deployment and identity verification.
But not everyone is happy about this move.
Google has contributed the Agent2Agent Protocol (A2A) to the Agentic AI Foundation (AAIF). For those who don’t know it, it is one of the emerging standards for AI-agent interoperability along with the Model Context Protocol (MCP).
A2A defines a common way for AI agents to discover one another, delegate work, and exchange tasks across framework and vendor boundaries. Google launched the protocol in April 2025, and later donated it to the Linux Foundation; AAIF said the project now has backing from more than 150 organizations and is deployed in production settings spanning supply chains, financial services, and mobile platforms. Pretty impressive for a protocol that’s just over a year old.
The purpose of A2A, according to the AAIF, is to enable developers and engineers to deploy multi-agent systems without blood, sweat, and tears. Before A2A came along, they had to deal with agents repeatedly not being able to talk with each other. “Agents built on different frameworks couldn’t hand off work to each other without custom integration code written specifically for each pairing. Every new vendor relationship required the same integration work from scratch. The cost wasn’t in the agents themselves but in the integrations between them.” Building bespoke links for each agent is both annoying and expensive.
A2A was built to solve that problem. It does this by defining “how agents communicate across framework and vendor boundaries. An agent publishes an agent card containing a structured description of what it can do and how to reach it. Other agents read that card, discover capabilities, and delegate tasks without a human brokering the handoff. The exchange is structured, observable, and framework agnostic.”
In addition, AAIF said A2A version 1.0, released in March, introduced multitenancy, version negotiation, multi-protocol bindings, and signed agent cards intended to support cryptographic identity verification.
That all sounds pretty spiffy, but making it easier for agents to pass work among themselves creates its own security and identity and access (IAM) problems. Mahesh Shanmugasundaram, Seekr‘s lead AI solutions architect, believes A2A brings with it the risk that unverified claims will travel and gain apparent authority through an agent chain.
Sure, Shanmugasundaram said, “Open protocols like A2A are an important step toward making agentic AI more interoperable and flexible. But the truth is, interoperability only expands that already existing trust gap. While the protocol standardizes the pipe, organizations decide what travels through it.”
He warned that A2A could create an “AI game of telephone,” in which each participant amplifies the previous agent’s confidence. A small hallucination at the beginning of a chain could therefore emerge several steps later as a highly authoritative-looking answer. Hmmm… AI giving very confident and very wrong answers. We’ve seen this before, haven’t we?
“In an A2A chain, each agent treats the prior agent’s output as 100% trusted input vs. a claim to be verified,” he said. “Once that assumption has been baked in, cascading failure becomes structurally worse than teams expect. Therefore, evidence-based evaluations and explainable output cannot be an afterthought,” Shanmugasundaram said. “Instead, it needs to be the default unit of exchange between agents. The success of the whole A2A system depends on it.”
Be that as it may, A2A is already being used in production. For example, Huawei has standardized A2A to link Celia, its OS-level AI assistant, and in-app agents across the HarmonyOS developer platform, while Tencent’s WeChat uses it to integrate with Huawei and other Android OEM assistants.
A2A isn’t just a mobile play. Google Cloud, as you’d expect, supports developing and deploying A2A agents through its cloud and Kubernetes offering. Microsoft Azure AI Foundry lets agents expose A2A endpoints and find external agents through standard discovery. In addition, AWS Bedrock AgentCore can host and operate A2A servers, so agents can collaborate across different frameworks and clouds. Finally, Google Cloud and PayPal are extending A2A into agentic commerce through the Agent Payments Protocol (AP2).
So, where do we go from here? AAIF’s hosting of A2A could help consolidate an increasingly fragmented agent interoperability landscape. The foundation said A2A’s goal is framework- and vendor-neutral communication, and noted that IBM’s Agent Communication Protocol merged into A2A in August 2025. So far, so good.
However, Shanmugasundaram’s critique underscores a distinction between interoperability and trustworthiness: standardized transport and discovery mechanisms do not establish that an agent’s output is accurate, well-sourced, or appropriate for the downstream action it may trigger. As organizations embrace agent-to-agent workflows, they will need to decide whether evidence, confidence metadata, traceability, and verification are merely optional application features, or mandatory properties of every handoff. Me? I see these as mandatory.
