AI Agent Interoperability: The A2A Protocol

The evolution of AI systems is shifting from isolated, monolithic models toward distributed, multi-agent architectures. As these systems grow in complexity, AI agent interoperability becomes a critical requirement. The Agent2Agent (A2A) protocol addresses this challenge by introducing an open, standardised approach for how AI agents discover, communicate, and collaborate across vendors and platforms. From an AI engineering perspective, A2A represents a foundational step toward building scalable and interoperable agent ecosystems.

What is the A2A Protocol? A New Standard for Agent Coordination

A2A (Agent2Agent) is an open protocol introduced by Google and contributed to the Linux Foundation to enable seamless interoperability between AI agents, regardless of their underlying framework or execution environment. It defines how agents advertise their capabilities through Agent Cards, exchange structured and task-oriented messages, and coordinate securely using established web standards such as HTTP, JSON-RPC, and Server-Sent Events.

By relying on familiar and widely adopted technologies, A2A lowers the barrier to integration and allows engineering teams to adopt agent-based systems without rethinking their entire infrastructure.

The Problem A2A Solves: Eliminating AI Silos

Traditionally, AI systems are tightly coupled to specific vendors or platforms, resulting in fragmented ecosystems and costly custom integrations. This approach limits scalability and makes multi-agent collaboration difficult. A2A directly addresses these issues by:

• Reducing Integration Overhead: A standard communication layer removes the need for bespoke adapters between agent systems.
• Enabling Modular Agent Design: Teams can build specialised agents that coordinate dynamically, rather than maintaining large, monolithic systems.
• Supporting Vendor-Agnostic Architectures: Organisations retain flexibility to evolve their AI stack as technologies and vendors change.

Engineering Value of A2A: Practical Benefits

From an AI engineer’s perspective, the real value of A2A lies in how it simplifies the construction of distributed, multi-agent systems. The protocol is designed with enterprise requirements in mind, supporting authentication, authorisation, long-running tasks, streaming updates, and multimodal content exchange.

• Scalable Multi-Agent Workflows: A2A enables agents to collaborate on complex workflows, such as data analysis pipelines or automated decision-making systems.
• Reduced Maintenance Costs: Standardised communication lowers long-term maintenance effort compared to custom-built integrations.
• Improved System Observability: Structured task-based messaging makes it easier to track agent interactions and system behaviour.

A Foundational Layer for Agentic Systems

Much like HTTP standardised communication for web services, A2A is positioning itself as a foundational protocol for agentic systems. It enables agents to discover each other dynamically and collaborate as part of a distributed intelligence layer, unlocking new possibilities for automation and system design.

Challenges and Considerations for Adoption

Despite its strong conceptual foundation, A2A is still in the early stages of ecosystem maturity. Tooling, developer experience, and trust or identity mechanisms between agents require further refinement, particularly for large-scale or high-risk deployments. Engineers adopting A2A should be prepared to invest in observability, security models, and supporting infrastructure as the standard evolves.