What Are Agent Cards? A Beginner's Guide to AI Agent Interoperability
Agent cards are JSON metadata enabling AI agent discovery and collaboration. Learn how they work, why SAP and Google use them, and their importance in 2026 multi-agent systems.
Introduction
Seventy-nine percent of enterprises are already adopting AI agents, yet most don't realize the critical infrastructure enabling these systems to talk to each other (McKinsey, 2026). Here's the problem: when your company deploys AI agents from SAP, Google Cloud, Salesforce, and ServiceNow all at once, how do they know what each other can do? Without a shared language, they can't collaborate.
Enter agent cards—the "business cards" of the AI world. They're small JSON files that describe what an agent can do, how to reach it, and what it needs to operate. They've become the foundation of the emerging multi-agent enterprise.
This guide explains what agent cards are, why they matter now, and how they're reshaping enterprise automation in 2026.
Key Takeaways
- Agent cards are JSON metadata files that describe AI agent capabilities, identity, and service endpoints, enabling discovery and interoperability between agents built by different vendors (A2A Protocol Community, 2026).
- 40% of enterprise applications will embed task-specific AI agents by 2026, up from less than 5% in 2025, making agent card standardization critical (Gartner, 2025).
- The A2A (Agent-to-Agent) Protocol, backed by 150+ organizations including Google, Microsoft, AWS, and SAP, uses agent cards as the foundation for secure, vendor-agnostic agent communication.
What Are Agent Cards?
An agent card is a JSON file that serves as an AI agent's "business card." According to the A2A Protocol Community, it describes an agent's identity, capabilities, skills, service endpoint, and authentication requirements—everything another agent needs to know before initiating contact (A2A Protocol Community, 2026).
Think of it like a LinkedIn profile, but instead of describing a person's work history and skills, it describes what an autonomous system can do. An agent card published by your customer service agent might list capabilities like "resolve billing disputes," "update shipping information," and "process refunds." When your sales agent needs to hand off a customer issue, it reads the customer service agent's card and knows exactly which functions to call.
The structure is simple but powerful:
- Identity: Who is this agent? What vendor built it?
- Capabilities: What functions can it perform?
- Endpoint: Where do I send requests?
- Authentication: What credentials do I need?
Agent cards are officially defined by the Agent2Agent Protocol, which is co-developed by Google and over 50 technology partners including SAP, Salesforce, ServiceNow, Intuit, Box, Cohere, and LangChain (Developers Google Blog, 2026). This standardization means your organization can mix and match best-of-breed agents without custom integration work.
Why Do Agent Cards Matter Now?
According to Gartner, 40% of enterprise applications will embed task-specific AI agents by 2026—up from less than 5% in 2025 (Gartner, 2025). That's a massive acceleration. But this explosion creates a scaling problem: without agent cards, you'd have to manually configure how every pair of agents communicates. It becomes a nightmare of custom connectors and brittle integrations.
Agent cards solve this by creating a standardized way for agents to advertise themselves. No manual wiring. No custom code. An agent publishes its card, and any other authorized system can read it and invoke its capabilities. This shift from siloed AI tools to interconnected agent networks fundamentally changes enterprise architecture.
Additionally, agent cards enable dramatic reductions in transaction costs—the time and effort involved in searching, contracting, and communicating between systems. Enterprises report 66% measurable productivity gains when deploying AI agents, with 57% achieving cost savings (Enterprise AI Adoption Survey, 2026). Agent card standardization is a key enabler of these gains because it removes friction from multi-agent workflows.
How Do Agent Cards Enable Agent-to-Agent Communication?
The magic of agent cards lies in the A2A Protocol, which uses them as the foundation for secure interoperability. Here's how it works:
Step 1: Agent publishes its card. An agent running on SAP's infrastructure publishes a JSON file describing what it can do. This file lives at a known endpoint—typically at https://[agent-service]/agent-card.json.
Step 2: Other agents discover the card. A Google Vertex AI agent needs to perform a task that SAP's agent specializes in. It sends an HTTP GET request to retrieve the card and reads the capabilities list.
Step 3: Agent inspects capabilities. The Google agent checks the card and confirms: "Yes, this SAP agent can handle dispute resolution. It requires OAuth token authentication. The endpoint is at /api/disputes."
Step 4: Agent initiates secure connection. The Google agent authenticates using the credentials specified in the card and makes a request to invoke the SAP agent's dispute resolution capability.
This entire handshake happens without human intervention—no IT tickets, no manual API documentation reviews, no engineering meetings. It's automation all the way down. For advanced patterns on orchestrating multiple agents across platforms, see our comprehensive breakdown of agent-to-agent communication.
Agent discovery happens automatically when agents publish their cards to a shared registry, enabling seamless peer-to-peer connections.
Currently, 23% of enterprises say they're scaling an agentic AI system somewhere in their organization, while 39% are experimenting (McKinsey, 2026). Most of those scaling agents are deploying them in only one or two functions, so there's still massive room for multi-agent coordination. Agent cards are the infrastructure that will enable this next wave of scaling.
Real Business Value: What's the ROI?
Numbers tell the story. Of enterprises that've deployed AI agents, 66% report measurable value through increased productivity (Enterprise AI Adoption Survey, 2026). Beyond that, 57% achieve cost savings, 55% report faster decision-making, and 54% see improved customer experience.
These gains compound when agents can talk to each other through standardized agent cards. Consider a dispute resolution workflow: traditionally, a human agent would gather information, consult multiple systems, and manually route the issue. With interoperable agents coordinated via agent cards, the dispute resolution agent automatically calls the accounting agent for transaction history, the customer service agent for interaction history, and the fraud detection agent for risk assessment—all within seconds.
Real use cases demonstrate this. SAP announced a new Dispute Resolution Agent that reasons through disputed transaction details and relevant business records to validate cases and propose solutions (SAP News Center, 2025). When this agent can invoke other SAP agents (and eventually agents from partners) via agent cards, the resolution time drops from hours to minutes. For a hands-on guide on wiring agents to SAP systems, see our detailed walkthrough on connecting agents to S/4HANA OData.
Agent Cards in Practice: SAP, Google Cloud, and Enterprise Adoption
The ecosystem is moving fast. Google released Vertex AI Agent Builder as part of its unified Gemini Enterprise Agent Platform, growing at 50% year-over-year (Google Cloud, 2026). For an in-depth exploration of building your first agent on Google's platform, check out our guide on launching a Vertex AI agent with A2A support. SAP, meanwhile, is on track to deploy 400+ AI features by the end of 2025, with new Joule Agents for disputes, accruals, digital service, and custom business workflows (SAP News Center, 2025).
But the real infrastructure shift is the A2A Protocol gaining production traction. As of early 2026, 150+ organizations are using the A2A Protocol in production, including AWS, Microsoft Azure, Google Cloud, Salesforce, SAP, ServiceNow, and dozens of independent AI providers (A2A Protocol Specification, 2026). Agent cards are the standard for all of them.
This matters because it means the agent you deploy from one vendor can natively talk to agents from others. No custom middleware. No proprietary connectors. Just standard JSON files and secure protocol. And the market is responding: the global AI agents market reached $7.6–7.8 billion in 2025 and is projected to exceed $10.9 billion in 2026 (Index Dev, 2026).
This explosive growth is driven by a simple realization: enterprises can't execute complex tasks with a single isolated AI agent. They need networks of specialized agents—one for customer service, one for finance, one for supply chain. Agent cards make these networks possible.
Enterprise AI agent networks run across distributed cloud infrastructure from multiple vendors, coordinated through standardized agent cards.
What Does the Future Hold for Agent Cards?
Agent cards will become infrastructure, not an optional feature. As Gartner forecasts, 40% of enterprise applications will embed task-specific AI agents by 2026. That level of adoption demands standardization. You can't manually integrate 40% of your app portfolio with custom connectors.
In 2026 and beyond, expect agent cards to evolve in one key direction: cryptographic attestation and safety alignment verification. An agent card won't just describe what an agent claims to do—it will cryptographically prove the model's weights, the version deployed, and safety alignment status. This matters because enterprises won't blindly trust an agent from an unknown vendor with access to sensitive data.
The shift from siloed AI tools to interconnected agent networks represents the next phase of enterprise automation. Organizations that adopt agent card standards early—by choosing SAP, Google, Salesforce, and other A2A-compliant platforms—will have a strategic advantage in scaling multi-agent workflows across their enterprise.
Frequently Asked Questions
How do agent cards differ from traditional APIs?
Traditional APIs require detailed documentation and custom client code written by developers. Agent cards are self-describing—an AI agent can read a card, understand capabilities, and invoke them without pre-written code. They're designed for machine-to-machine communication at scale.
Do I need to understand agent cards as a business user?
Probably not the technical details. But you should know they exist because they're the infrastructure your IT team will rely on to connect SAP, Google Cloud, Salesforce, and other platforms. When your CIO says "we're adopting the A2A Protocol," they're talking about standardized agent cards behind the scenes.
Can any AI agent use agent cards?
Not yet. Your agent must support the A2A Protocol specification. Google, SAP, Salesforce, ServiceNow, and 150+ other organizations already support it. Smaller vendors are catching up, but proprietary agent platforms still exist.
What's the difference between agent cards and the A2A protocol?
The A2A Protocol is the rulebook for how agents communicate over the network. Agent cards are the metadata format that agents use within that protocol. Think of it like: the A2A Protocol is HTTP, and agent cards are JSON.
How secure are agent cards?
Agent cards themselves are just JSON files—they're not secret. Security comes from the A2A Protocol's authentication and authorization mechanisms, which verify credentials and control what each agent can access. Think of a card as a public resume; the actual permissions are controlled separately.
Conclusion
Agent cards are the bridge between isolated AI agents and true multi-agent enterprises. They're not a buzzword—they're infrastructure that 40% of enterprise applications will rely on by 2026.
For business users, the takeaway is simple: if your organization is deploying AI agents across multiple platforms, agent cards matter. They reduce integration friction, enable real-time collaboration between systems, and unlock the productivity gains that 66% of enterprises are already capturing.
The market will demand interoperability. By 2026, proprietary agent ecosystems will be at a disadvantage. Standards-based, A2A-compliant agents from SAP, Google, Salesforce, and their partners will become the baseline.
If you're building your multi-agent strategy, start with platforms that support agent cards. Your future self will thank you.
Next Steps
Ready to move from theory to practice? We've covered the foundation—now it's time to build:
- Start with Vertex AI: Follow our step-by-step guide to deploying your first A2A-compatible agent on Google Cloud
- Connect to SAP: Learn how to wire agents to S/4HANA OData systems without the complexity
- Orchestrate at scale: Explore patterns for multi-agent coordination across your enterprise
Want to go deeper? Explore Agents with SAP for more detailed implementation guides and best practices.