Microsoft Adopts Google's Open Protocol to Enable AI Agent Collaboration

Microsoft has announced its support for Google's recently launched open protocol, Agent2Agent (A2A), which enables AI-powered agents to communicate and collaborate across different clouds, applications, and services. This integration will be available on Microsoft's AI development platforms, Azure AI Foundry and Copilot Studio.

The A2A protocol allows semi-autonomous AI agents to exchange goals and invoke actions securely, facilitating complex multi-agent workflows that span internal systems, partner tools, and production infrastructure. For example, an AI agent developed by Microsoft could schedule meetings while a Google agent drafts email invitations, demonstrating cross-platform collaboration.

Microsoft has also joined the A2A working group on GitHub to actively contribute to the protocol and tooling, emphasizing its commitment to open standards and interoperability in AI development. This move supports the broader industry trend toward shared agent protocols, which enhance adaptability and observability in software design.

The adoption of A2A comes amid growing enterprise interest in agentic AI technology, which is projected to expand significantly in the coming years. According to market research, the AI agent segment is expected to grow from $7.84 billion in 2025 to $52.62 billion by 2030, reflecting strong demand for AI-driven productivity tools.

Previously, Microsoft integrated support for Anthropic’s MCP standard in Copilot Studio, aligning with other major AI providers like Google and OpenAI. This demonstrates Microsoft's strategy to support multiple open protocols, fostering a collaborative AI ecosystem that spans diverse platforms and services.

Implications for Developers and Enterprises

By adopting A2A, Microsoft empowers developers to build AI agents capable of interoperating across ecosystems, enhancing flexibility and productivity. Enterprises can leverage these capabilities to automate complex workflows that involve multiple AI agents, improving efficiency while maintaining governance and compliance standards.

This collaborative approach to AI agent design marks a significant step toward the next generation of software that is adaptive, observable, and integrated seamlessly into the flow of work. It also highlights the importance of open standards in accelerating AI innovation and adoption across industries.