Google has launched Agent2Agent (A2A), a new open-source protocol designed to let AI agents from different vendors and systems work together seamlessly.
Announced with support from over 50 tech partners—including Salesforce, SAP, ServiceNow, and MongoDB—A2A aims to eliminate the fragmentation that currently limits enterprise AI deployments.
The protocol enables agents to exchange information securely, coordinate tasks, and operate across platforms without custom integrations.
Built on standard web technologies like HTTP and JSON, A2A is enterprise-focused and community-driven.
With a production-ready version expected later this year, Google is inviting developers and enterprises to help shape what could become the foundational protocol for multi-agent AI collaboration.
A Clear Fix to a Costly Problem
Most enterprise AI systems today operate in isolation. One agent handles customer service, another manages data queries, and a third might oversee backend automation. But because these agents can’t communicate across platforms, businesses face unnecessary costs, duplicated efforts, and limited automation capabilities.
Agent2Agent changes this. It introduces a universal way for AI agents to discover one another, share capabilities, and coordinate actions in real time, regardless of origin or purpose.
It provides a shared communication layer that removes the need for expensive, custom-built bridges between systems.
The protocol defines four core functions:
- Capability Discovery: Agents publish what they can do using JSON-based “Agent Cards,” making it easy for others to find the right collaborator for a given task.
- Task Management: A full lifecycle system for assigning, tracking, and completing tasks between agents.
- Collaboration: Agents can jointly handle complex, multi-step workflows with synchronized data and context.
- User Experience Negotiation: When multiple agents contribute to a user-facing experience, they collaborate on delivering a unified output.
Open, Extensible, and Built for the Enterprise
Unlike proprietary frameworks that tie users to a single vendor, A2A is open source. Anyone can inspect the code, contribute improvements, and tailor the protocol to suit specific needs. This approach fosters a growing ecosystem where interoperability is the rule, not the exception.
Importantly, A2A doesn’t aim to replace existing standards like Anthropic’s Model Context Protocol (MCP) or Microsoft’s AutoGen.
Instead, it operates above them, acting as a coordination layer that unites disparate agents regardless of the lower-level protocols they use.
In this way, it acts as both a bridge and a catalyst—uniting systems while accelerating innovation.
For enterprises, this means freedom: freedom to choose best-in-class tools, freedom to connect those tools without paying for complex integrations, and freedom to scale AI projects faster, with less risk and less vendor lock-in.
Why A2A Will Reshape Enterprise AI
Enterprise AI is moving beyond isolated automation and into system-wide intelligence. That transition requires agents that can cooperate across departments and platforms—something that’s never been straightforward until now.
Take a supply chain example: a logistics agent identifies a shipping delay, a CRM agent checks how many customers are affected, and an operations agent recalculates fulfillment timelines. With A2A, these agents don’t need human intervention or middleware to act—they simply communicate and coordinate directly.
The benefits are immediate:
- Faster responses to dynamic conditions
- Greater process automation across teams
- Lower cost and effort for system integration
- More consistent user and customer experiences
Analysts at Deloitte have emphasized A2A’s potential to unify workflows and reduce integration overhead—a longstanding challenge for enterprises scaling AI.
What Enterprises Should Do Right Now
Agent2Agent is a strategic opportunity. To get the most of it, enterprises should begin laying the groundwork today.
Audit Your Existing Agents: Understand what agents are in use and where collaboration is blocked.
Target Friction Points: Identify workflows that require manual handoffs or custom integrations—these are ideal candidates for A2A implementation.
Explore the A2A Specification: Available on GitHub, the protocol is open to inspection, testing, and contribution.
Run Pilot Programs: Start small by connecting two or more agents using A2A in a controlled setting, then scale based on results.
Upskill Internal Teams: Developers and architects will need to understand multi-agent system design and the principles behind A2A for long-term success.
Adoption doesn’t require a full overhaul. A2A can be integrated incrementally, unlocking benefits as each new agent is connected to the network.
Key Takeaways
- Google launched Agent2Agent (A2A), an open-source protocol for communicating and working with AI agents from different vendors.
- Over 50 major tech companies like Salesforce, SAP, and ServiceNow are supporting the protocol, signaling wide industry adoption.
- A2A eliminates integration barriers by using standard technologies (HTTP, JSON) to unify AI systems across platforms.
- Enterprises can automate complex workflows without custom code by enabling direct agent-to-agent coordination.
- A production-ready version is coming in 2025, and Google is inviting developers to contribute to the protocol now.
Dileep Thekkethil
AuthorDileep Thekkethil is the Director of Marketing at Stan Ventures, where he applies over 15 years of SEO and digital marketing expertise to drive growth and authority. A former journalist with six years of experience, he combines strategic storytelling with technical know-how to help brands navigate the shift toward AI-driven search and generative engines. Dileep is a strong advocate for Google’s EEAT standards, regularly sharing real-world use cases and scenarios to demystify complex marketing trends. He is an avid gardener of tropical fruits, a motor enthusiast, and a dedicated caretaker of his pair of cockatiels.