Agent2Agent: Revolutionizing Multi-Agent Collaboration in Copilot Studio

Key insights

• Agent2Agent (A2A) is an open protocol that enables AI agents to communicate, collaborate, and work together across different platforms, clouds, and organizations, improving agent interoperability.


• Copilot Studio and Azure AI Foundry will soon support A2A, allowing developers to build advanced multi-agent workflows while maintaining security, governance, and service-level agreements (SLAs).


• The rise of agentic systems marks a shift from simple bots to intelligent agents that can act autonomously and interact with each other using protocols like A2A and Model Context Protocol (MCP).


• A2A provides structured communication for agents—exchanging goals, managing state, invoking actions, and returning results securely. It supports popular developer tools such as Semantic Kernel and LangChain, operating within enterprise-grade safety frameworks.


• This move aligns with Microsoft’s commitment to openness: supporting developers in building interoperable agents that scale across vendors, clouds, and data silos without vendor lock-in.


• The future of software lies in collaborative agent networks—adaptive by design—where intelligence seamlessly operates across domains. Microsoft continues contributing to open protocols like A2A and MCP to advance this vision for enterprise AI.

Introducing Agent2Agent: A New Era for Copilot Studio and Azure AI

Microsoft's recent announcement marks a pivotal moment for enterprise AI, as the company introduces support for the Agent2Agent (A2A) protocol within its Copilot Studio and Azure AI Foundry platforms. This development builds upon the earlier integration of the Model Context Protocol (MCP), signaling a commitment to open standards and interoperability in the fast-evolving world of artificial intelligence. Notably, Microsoft has also joined the A2A working group on GitHub, aiming to shape the protocol’s specification and tooling for industry-wide adoption.

Over the past year, AI agents have rapidly progressed from experimental features to indispensable business tools. These agents now move beyond simple prompt-and-response mechanisms, taking on autonomous roles within complex enterprise systems. With this shift, the need for agents to communicate across different platforms and organizations has become increasingly critical.

The Rise of Multi-Agent Systems in the Enterprise

Organizations are already leveraging Microsoft’s AI offerings at scale. According to Microsoft, Azure AI Foundry is now utilized by more than 70,000 enterprises and digital-first companies. This adoption includes prominent names such as Atomicwork, Epic, and LG Electronics. Within just four months, over 10,000 organizations have started using the Agent Service to build, deploy, and manage agentic systems. Furthermore, more than 230,000 organizations—including 90% of the Fortune 500—have incorporated Copilot Studio into their workflows.

As AI agents become more sophisticated, the demand for seamless collaboration between them grows. Microsoft’s support for open protocols like A2A is designed to address this challenge by enabling agents to interact securely and efficiently across clouds, platforms, and organizational boundaries. This approach reflects a broader industry movement toward shared protocols that foster compatibility and openness.

Balancing Openness, Security, and Control

Microsoft’s vision emphasizes openness while maintaining robust security and governance. By supporting A2A, developers can utilize familiar tools such as Semantic Kernel or LangChain without sacrificing interoperability. All agent interactions are protected by enterprise-grade safeguards, including Microsoft Entra, mutual TLS, Azure AI Content Safety, and comprehensive audit logs. This ensures that as agent ecosystems grow more distributed, safety and accountability remain paramount.

However, achieving this balance is not without challenges. Enterprises require agents to orchestrate tasks that span multiple vendors, clouds, and data silos. They expect full control, visibility, and trust—while avoiding vendor lock-in. Microsoft addresses these needs by building trust into Azure AI Foundry by default and prioritizing compliance and observability as first-class features.

The Benefits and Tradeoffs of Open Agent Protocols

The introduction of A2A brings clear advantages. Azure AI Foundry customers can now construct complex, multi-agent workflows that connect internal copilots, partner tools, and production infrastructure—all while maintaining strict governance and service-level agreements. Meanwhile, Copilot Studio agents gain the capability to securely invoke and collaborate with external agents, even those built on other platforms.

Nonetheless, there are tradeoffs to consider. While open protocols increase flexibility and foster innovation, they also introduce new complexities in ensuring consistent security and performance across diverse environments. Microsoft’s approach aims to mitigate these risks by embedding safeguards and promoting industry collaboration through initiatives like the A2A working group.

Looking Forward: The Future of Agentic Computing

Microsoft views agentic computing not as a passing trend, but as a fundamental transformation in software design and business operations. By contributing to open standards and providing resources such as Semantic Kernel samples in .NET and Python, Microsoft encourages both professional and citizen developers to experiment with multi-agent workflows. The upcoming public preview of A2A in Foundry and Copilot Studio will further advance this vision.

Ultimately, Microsoft’s strategy is to create an open, adaptive, and collaborative ecosystem where intelligent agents can operate seamlessly across boundaries. As agentic systems continue to evolve, balancing openness, security, and ease of integration will remain central challenges—but Microsoft’s ongoing investments suggest a strong commitment to making this vision a reality for enterprises worldwide.

Keywords

Agent2Agent Multi-Agent App Copilot Studio AI collaboration productivity automation integration smart agents