Google’s A2A Protocol Could Reshape SAP’s AI Strategy

Google has introduced the A2A (Agent-to-Agent) protocol, a new open standard designed to make it easier for AI agents to interact across platforms, organizations, and ecosystems—including within complex SAP environments. The protocol defines a shared method for agents to discover, authenticate, and communicate with one another, which is increasingly critical as enterprise AI tools like SAP Joule become embedded throughout core business systems. The initiative is governed by the newly formed A2A Alliance and already includes over 30 participating organizations, including major hyperscalers, software vendors, and systems integrators.

At its core, A2A addresses a rising concern in enterprise AI: the lack of interoperability. While domain-specific AI tools now exist across a wide spectrum of software applications, most operate in isolation. Google’s A2A specification aims to provide a way for these agents to advertise their capabilities, exchange tasks, and securely collaborate across organizational boundaries.

For SAP customers, the potential is significant. A2A offers a way for agents like SAP Joule to go beyond system-specific queries and become orchestrators of cross-application workflows. In this model, Joule could delegate a task to a Google Workspace agent, then pull data from Salesforce or ServiceNow, all through a shared communication layer.

From Protocol to Platform Strategy

The A2A specification includes mechanisms for agent registration, authentication, and capability discovery. It is based on established standards such as HTTP and JSON-RPC, allowing easy adoption without requiring deep changes to enterprise architecture. The protocol is hosted on GitHub and is open for contributions from the broader developer community.

For enterprise architects and developers, this means they can start building agents that comply with A2A now. Agents can define what tasks they can perform, expose endpoints to handle requests, and even chain operations with other agents. Google frames A2A as a “universal handshake” for autonomous systems.

Though early, the protocol could eventually standardize how AI agents collaborate across systems, much like HTTP standardized communication across the web. Google suggests that it could reduce custom integration costs and simplify AI governance if it is adopted broadly.

SAP’s early support gives the protocol credibility and relevance for ERP-centric organizations. Walter Sun, SVP & Global Head of AI Engineering at SAP, said: “SAP is committed to collaborating with Google Cloud and the broader ecosystem to shape the future of agent interoperability through the A2A protocol—a pivotal step toward enabling SAP Joule and other AI agents to seamlessly work across enterprise platforms and unlock the full potential of end-to-end business processes.”

What This Means for SAPinsiders

AI agents will begin working not just for users, but with each other. As SAP Joule and other enterprise agents adopt the A2A protocol, they will be able to offload tasks, coordinate actions, and resolve business processes across applications without manual intervention. This expands the role of the enterprise IT team from building integrations to overseeing a network of intelligent agents that cooperate autonomously.

AI agent interoperability is becoming a strategic differentiator in a growing market. As enterprise adoption of generative AI accelerates—by some projections, over $140 billion in enterprise AI spending by 2027—Google, SAP, and other vendors are all pushing agentic platforms. However, A2A stands out by addressing the biggest challenge: cross-platform collaboration. For SAP customers, aligning with A2A-ready platforms may become key to future-proofing their AI investments.

Select vendors based on openness, integration capabilities, and standards alignment. IT decision-makers evaluating agent-based solutions should look beyond interface design and LLM quality. Instead, focus on whether agents support open protocols like A2A, provide secure endpoint interfaces, and demonstrate readiness for enterprise-wide collaboration. As with early APIs and service buses, these characteristics are likely to determine scalability and long-term success.