Google's New AI Protocol Lets Digital Workers Team Up

Think of A2A as a shared language for AI systems. It lets agents from different vendors work together - whether they're booking meetings, ordering supplies, or hiring staff.

The timing fits a clear trend. Companies already use AI agents to handle daily tasks. But these agents work alone, stuck in their own systems. A customer service agent can't talk to a scheduling agent. A hiring agent can't work with background check software.

A2A fixes this. It creates rules for how agents share information and tackle jobs together. The system works with standard web tools and existing security setups.

The protocol brings real flexibility. Agents can handle quick tasks or complex projects that take days. They can work with text, audio, or video. They can even loop in humans when needed.

Here's how it works: Each agent has an "Agent Card" - like a digital resume showing what it can do. When one agent needs help, it broadcasts its request. Other agents can jump in if they have the right skills. The system tracks progress and keeps everyone updated.

Take hiring a software engineer. Today, that means jumping between systems. With A2A, one agent finds candidates while another checks their background and a third sets up interviews. The agents work as a team, even if different companies built them.

MongoDB sees this enabling new retail and factory systems. SAP plans to plug it into their Joule AI platform. ServiceNow thinks it will transform how companies handle support tickets.

The protocol isn't just for tech companies. Consulting giants Deloitte, KPMG, and Accenture have signed up. They'll use A2A to help big clients adopt AI faster.

Key tech players praise the open approach. Salesforce plans to use it in their "Agentforce" platform. Atlassian will connect it to their Rovo agents. PayPal sees it sparking new ways to handle payments.

Google built A2A to work with other standards. It pairs with Anthropic's Model Context Protocol (MCP), which helps agents use tools. If MCP is the socket wrench, A2A is how mechanics talk while fixing a car.

Security got special attention. A2A works with enterprise authentication systems from day one. It lets companies control how agents share data and what they can access.

The system handles different types of AI agents. Some show their work, others keep it private. A2A doesn't care - it focuses on getting the job done through clear tasks and updates.

Google developed A2A based on real customer needs. The company saw businesses struggling to connect AI systems across platforms. Rather than build a closed solution, they made it open source.

Developers can start working with A2A now. Google released sample code for popular frameworks like LangGraph, CrewAI, and Genkit. A full production version launches later this year.

Industry watchers note how A2A could shape enterprise AI. Just as Kubernetes set standards for cloud apps and OAuth simplified secure login, A2A could make agent collaboration routine.

The broad support matters. When tech giants agree on a standard, it tends to stick. Companies building AI systems today should watch A2A closely.

Why this matters:

• We're seeing the birth of true AI teamwork. Just as email standards let humans talk across platforms, A2A could create networks of AI agents that actually work together.
• The protocol tackles real business needs: security, long-running tasks, and working across different systems. This isn't a tech demo - it's built for actual companies doing actual work.

Read on, my dear:

Google: Announcing the Agent2Agent Protocol (A2A)