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Google AI recently announced Agent2Agent (A2A)an open protocol designed to facilitate secure, interoperable communications between AI agents established on different platforms and frameworks. By providing a standardized approach to proxy interaction, the A2A aims to simplify tasks involving professional AI agents to accomplish different complexities and durations.
A2A addresses key challenges in the AI field: the lack of a common mechanism for agents to discover, communicate and coordinate among supplier ecosystems. In many industries, organizations often deploy multiple AI systems for specific functions, but these systems do not always integrate smoothly. A2A aims to close this gap by providing a common set of rules for proxy interoperability so agents created by different teams or companies can work without custom integration.
The prominent feature of A2a is Enterprise-level focus. Agreement support Long-term running tasks In days, weeks, or even months, such as supply chain planning or multi-stage recruitment. It’s also suitable Multimodal collaborationso AI agents can share and process text, audio, and video in a unified workflow. By using Agent Card In JSON format, the agent can advertise its features, security permissions, and any relevant information required to handle tasks. This approach allows each agent to quickly evaluate whether it can perform a given task, request other resources, or delegate responsibility to other capable agents.
Safety It is another core aspect of A2A. AI systems often process sensitive data, such as personal information in recruitment or customer records in finance. To meet these requirements, A2A and OpenApi-level authentication Standard, implement role-based access control and encrypted data exchange. This approach is designed to ensure that only authorized agents with the correct credentials and permissions can participate in critical workflows or access protected data flows.
To guide its development, A2A is built around Five core design principles:
- Agent first: By default, the proxy does not share memory or tools. They operate independently and communicate clearly to exchange information.
- Comply with the standards: This protocol uses widely adopted web technologies such as HTTP, JSON-RPC and Server Quantity Events (SSE) to minimize developer friction.
- Safe by default: Built-in authentication and authorization measures are designed to protect sensitive transactions and data.
- Handle short and long tasks: A2A supports short interactions (such as fast information requests) and extended processes that require continuous collaboration.
- Modal agility: Agents can handle text, video, audio, or other data types by sharing structured task updates in real time.
From Technical perspectiveA2A can be seen as a complement to other emerging standards for AI multi-institutional systems. For example, Human Model Context Protocol (MCP) Focus on how different language models handle shared contexts during multi-agent inference. The focus of A2A is on the interoperability layer, ensuring that agents can safely discover each other and once the model is ready to exchange data or coordinate tasks. This combination of context sharing (MCP) and proxy communication (A2A) can form a more comprehensive basis for multi-institutional applications.
An example of an A2A Reality Application Application is Hiring process. One agency may screen candidates based on specific criteria, another can schedule an interview, and the third can manage background checks. These professional agents can communicate through a unified interface, synchronize the status of each step and ensure that relevant information can be safely passed.
Google has open source A2A to encourage community participation and standardization in the AI industry. Major consulting and technology companies, including BCG, Deloitte, Cognizant and Wipro, contributed to their development with the aim of improving interoperability and security. By adopting this collaborative approach, Google’s goal is to lay the foundation for a more flexible and efficient multi-agent ecosystem.
Overall, A2A provides organizations with a structured way to integrate professional AI agents, allowing them to exchange data securely, manage tasks more effectively, and support a wide range of enterprise requirements. As AI continues to expand into all aspects of business operations, protocols such as A2A may help unify different systems, thereby facilitating more dynamic and reliable workflows.
Check Technical details and Google blog. All credits for this study are to the researchers on the project. Also, please feel free to follow us twitter And don’t forget to join us 85k+ ml reddit.
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Asif Razzaq is CEO of Marktechpost Media Inc. As a visionary entrepreneur and engineer, ASIF is committed to harnessing the potential of artificial intelligence to achieve social benefits. His recent effort is to launch Marktechpost, an artificial intelligence media platform that has an in-depth coverage of machine learning and deep learning news that can sound both technically, both through technical voices and be understood by a wide audience. The platform has over 2 million views per month, demonstrating its popularity among its audience.
