Google’s Agent2Agent Protocol Launches as the “HTTP for AI,” Unlocking Cross-Platform Collaboration April 15, 2025 — Google has unveiled the Agent2Agent (A2A) protocol, a groundbreaking open-source framework designed to enable seamless communication between AI agents across different platforms, vendors, and frameworks. Backed by over 50 major tech firms—including Salesforce, SAP, PayPal, Atlassian, and ServiceNow—the protocol aims to standardize AI agent collaboration much like foundational internet protocols such as HTTP revolutionized data exchange.

Breaking Down Silos in Enterprise AI The A2A protocol addresses a critical bottleneck in enterprise AI adoption: the inability of specialized agents to work together. Organizations today deploy AI agents for tasks ranging from customer support to supply chain optimization, but these systems often operate in isolation due to proprietary APIs and incompatible data formats. For example, a customer service chatbot might lack access to billing data controlled by a finance agent, forcing manual intervention or costly custom integrations.

A2A eliminates these silos by providing a universal language for agents to discover, communicate, and collaborate securely. “Standard protocols are essential for enabling agentic interoperability, particularly in connecting agents to each other across vendor ecosystems,” Google stated in its April 9 announcement. The protocol’s open-source nature ensures developers can integrate it without vendor lock-in, fostering a competitive ecosystem where agents from Google, Salesforce, or niche startups can interoperate effortlessly.

How A2A Works: The Technical Backbone At its core, A2A leverages familiar web standards:

• HTTP/SSE for real-time communication
• JSON-RPC 2.0 for remote procedure calls
• Agent Cards (public JSON profiles) that advertise an agent’s capabilities and endpoints

This design allows agents to negotiate interactions dynamically. For instance, an HR recruiting agent could query a knowledge base agent for candidate details, while a logistics agent coordinates delivery schedules with a supplier’s AI—all without predefined integrations.

Enterprise Impact: From Customer Service to Cross-Company Workflows Early adopters highlight transformative use cases:

• Customer Support: A chatbot delegates billing inquiries to a finance agent, which securely accesses ERP systems via A2A.
• Supply Chain Optimization: Procurement agents from different vendors collaboratively adjust orders during disruptions, using real-time inventory data.
• Cross-Company Collaboration: Agents from separate enterprises negotiate contract terms directly, reducing manual oversight.

Google’s protocol also complements Anthropic’s Model Context Protocol (MCP), which standardizes how agents access tools and data. Together, they solve the “MxN problem” of integrating M AI models with N tools, reducing integration costs.

Industry Reactions and Future Outlook The protocol has garnered support from Accenture, Deloitte, and other global consultancies, signaling rapid enterprise adoption. “A2A isn’t just a technical upgrade—it’s the foundation for AI agent networks that think and act as teams,” said Sid Saladi, an AI product strategist.

Analysts predict A2A could accelerate AI agent deployment by 30-50% in enterprises by 2026, as it reduces reliance on custom coding and enables best-of-breed agent combinations. However, challenges remain, including ensuring compliance with evolving data privacy regulations and managing agent conflict-resolution protocols.

The Bigger Picture By positioning A2A as an open standard, Google aims to replicate the success of protocols like HTTP in unifying fragmented systems. As enterprises increasingly rely on multi-agent AI ecosystems, A2A’s role as a “collaboration layer” could redefine how businesses automate complex workflows—from hiring to global logistics.

With contributions from Google’s partner ecosystem, the A2A protocol is now available on GitHub, inviting developers to contribute to its evolution.