Building Enterprise Intelligence: A Guide to AI Agent Protocols for Multi-Agent Systems

In this article we discuss: 

• The Evolution of Enterprise Interoperability

• Understanding Core AI Communication Protocols

• Strategic Implications for CIOs and CTOs

• Building Your Own AI Agent Strategy

• Unlocking Collaborative Intelligence

We often marvel at the bustling highways of modern cities; cars, trucks, and buses zipping from one destination to another. When you really think about it, it’s incredible how quickly vehicles get us where we need to go. 

But the real, and often underappreciated, star keeping everything running smoothly is that unseen network of roads, traffic signals, and well-organized infrastructure. It’s somewhat the same with AI.

Agents have been getting all the attention, and for good reason, but their true power comes from the underlying highways—communication protocols—that let agents interact and transform organizations. 

For leaders guiding companies through this new tech transformation, understanding and strategically adopting these protocols isn’t just about keeping pace but better understanding the risks and advantages of their agents. 

Let’s explore the emerging standards that govern agent communication. Demystify their roles, how they work together for greater impact, and uncover what this means for your organization. 

The Evolution of Enterprise Interoperability: From APIs to AI Protocols

The early days of the internet often felt like a new frontier, where different software applications were like isolated towns with no easy way to communicate or share resources. For those towns to flourish, they needed connection. They needed roads. Application programming interfaces, or APIs, became those roads. 

APIs became the connection these digital towns needed, allowing them to exchange data and information seamlessly. They laid the groundwork for our interconnected digital world, making it possible for your favorite apps to talk to each other, businesses to automate processes, and developers to build innovative new services. 

And now that’s evolved. The next generation of digital superhighways won’t be for human-driven interaction but agent-driven collaboration. That’s where AI protocols come in and many leaders are already thinking about it.

At Workday DevCon 2025, Dean Arnold, VP, Agent System of Record, shared how agent communication is on the horizon at the company, “We’re going to make capabilities in our platform available through MCP and through A2A. We want agents to collaborate with agents. We want tools and APIs and data to be surfaced in MCP.”

In other words, Workday will use model context protocol (MCP) to provide AI agents with the necessary business data and access to tools, and agent-to-agent protocol (A2A) to enable these AI agents to communicate and work together seamlessly within the Workday platform.

These agent-driven superhighways will require advanced communication. Arnold drove home that leaders will need to stay informed on evolving protocols and select a platform that aligns with industry leaders, ensuring interoperability remains central.

AI protocols are the key to making sure things run smoothly, enabling agents to work together autonomously.

Understanding the Core AI Communication Protocols: The Roads Less Traveled (Until Now)

Let’s dive into the top protocols—MCP, ACP, and A2A—and get into what makes them different, which works best for your business, and how they work together. 

Model Context Protocol (MCP): Fueling Intelligent Action

If APIs are the basic roads connecting isolated digital towns, think of model context protocol (MCP) as the on-ramps, off-ramps, and real-time navigation systems built directly into those highways. 

Introduced by Anthropic, MCP is an open protocol focused on how large language model (LLM)-based applications connect to data sources and tools. MCP simplifies how LLMs get their context—things like prompts, files, data, streams—from all sorts of places, whether it’s local files, remote databases, or external services. This allows LLms to easily call on specific tools and pull in outside data exactly when they need it. 

Think of agents as cars and MCP as the GPS that shows it the main route and highlights detours for specific destinations (tasks), like finding a gas station (a tool) or where to avoid traffic jams using real-time updates (external data). 

Agent Communication Protocol (ACP): Local-First Orchestration

If MCP helps individual agents navigate data and tools, agent communication protocol (ACP) is like a private, highly optimized road system for agents in specific environments—like a restricted access road for a private company. 

ACP lets agents communicate with each other and coordinate their actions in local environments. Kind of the way smart home devices communicate and sync their actions through one hub. It standardizes how agents in a local environment talk to each other and removes barriers caused by inconsistent interfaces. 

It creates a space where agents can share skills, activities, and roles. They can communicate through quick messages, making it simple to collaborate and find other tasks. 

Agent-to-Agent (A2A) Protocol: Enabling Cross-Platform Collaboration

With different agents constantly on the move, how do they interact between vendors?  Agent-to-agent (A2A) protocol is like the interconnected superhighway system that allows agents to journey together, even if they come from different manufacturers or are fueled by different systems. 

Google introduced A2A to streamline how agents from different companies share and manage tasks. It’s like a company creating a universal language for self-driving cars that can be used for all brands. No matter the company, cars could share traffic updates, routes, and help each other during long drives. That’s what A2A does for agents. 

A2A allows agents working together across different companies to start and do tasks, send live updates, and handle files, which makes managing work flexible.

Strategic Implications for CIOs and CTOs: Why Owning These Highways Matters

For technology leaders, knowing these protocols is more than just tech talk. Controlling agent systems is key to finding new ways to be efficient and make smarter decisions. And having leaders at the helm ensures agents are used safely and wisely. Here’s why understanding these connections is so important in today’s digital world: 

1. Unlocking New Levels of Automation and Efficiency. These new protocols help agents work together smoothly, leading to full end-to-end automation. This means many business tasks become faster and simpler. In HR, for instance, an agent can find stellar candidates, then work with other agents to schedule interviews and run background checks. Using MCP to get HR data, the agents greatly speed up the hiring process. 

2. Enhanced Data Utilization and Decision Making: MCP helps AI make smarter, more accurate decisions. It feeds real-time, organized data directly into LLMs to ensure their actions and answers use current, correct information. For example, AI tools can use MCP to connect to databases, letting them run complex searches or analyze data from simple questions. Companies like Paypal have rolled out this protocol to improve agentic commerce and enable AI-driven capabilities for merchants. 

3. The Human-in-the-Loop and Ethical AI: Building Trust on the Road Ahead: As agents become more independent, ensuring human oversight and ethical use is vital to building trust. These new protocols help achieve this by making agent actions transparent. This means humans can see how agents are operating and step in when needed, much like a driver overseeing an autonomous vehicle. Transparency is key, especially for businesses that use agents for complex or sensitive information. 

   Think of a multi-agent system handling customer support. The initial agent receives a customer query, then uses A2A to delegate tasks. It tags in an agent to use MCP to pull customer history, another to check product information, and a third to draft a response. Throughout this process, a human can monitor the workflow and step in when agents encounter unusual problems or require approval for sensitive responses. So while AI automates and streamlines, human teams maintain control and can guide the process, fostering a trustworthy AI partnership.

4. Cybersecurity and Governance: Securing Your Digital Infrastructure: Much like managing a large human workforce requires security, so does managing agents. CIOs and CTOs have to implement robust access controls, continuous monitoring, and thorough auditing. Agents can have access to all kinds of sensitive data and a compromised system could spell chaos. Both MCP and A2A prioritize security, leveraging host-mediated security, sandboxing, and standard web security like OAuth 2.0 and API key authorization. But even with these built-in features, careful design and ongoing vigilance are still key to keeping AI systems secure. 

Building Your AI Agent Strategy: Paving the Way Forward 

For CTOs and CIOs, building a successful agent strategy means carefully integrating these new protocols into your enterprise AI approach. Here are a few guidelines:

• Start by clearly defining the problems you want to solve. Focus on how these solutions will help your users. Identify specific business challenges where agents can make a real difference. Maybe consider using MCP to connect LLMs to internal business systems like HR platforms to automate tasks like lead generation or employee onboarding.

• Consider how different agents work together. A2A allows agents from various systems and vendors to communicate and share tasks. This means you can create complex workflows, like a sales agent triggering a contract generation by a legal agent. This kind of collaboration between agents is crucial but also presents its own challenges. Consider what data will be shared between agents, how customers will interact with them, and how those interactions may affect how agents work together.

Remember, security and governance are not afterthoughts. Agents need a thorough framework to monitor and audit workflows. By including security and governance in your strategy, you can build a scalable and trustworthy AI infrastructure into your organization.

The Future Landscape: Unlocking Collaborative Intelligence on the AI Superhighway

We've seen this before, right? For decades, APIs helped applications communicate. This allowed companies to expand their reach. Now, agent protocols offer the same possibilities.

"We had decades of experience with APIs, which previously allowed applications to communicate with each other, and the builders from individuals to companies to access data and functionalities,” Kathy Pham, VP of AI at Workday. 

“This opened up possibilities for companies to expand beyond their own boundaries, extending their reach even more. Agent protocols have the same possibilities—they allow communication between agentic systems, allowing individuals and companies to connect agents to yield more effectiveness than alone. These are protocols that empower collaboration globally. Those who create the protocols hold a certain power, and more importantly, those who know how to use those protocols with the right partners, connecting the right agents, will build solutions well beyond what we each can do alone."

The rise of MCP, ACP, A2A shows a strong industry push for standardization and interoperability. While there's a natural concern about fragmentation, the real opportunity is how these standards work together. 

This isn't just about avoiding digital islands; it's about building a vast, interconnected continent of intelligence.

To ensure this collaborative future, tech leaders should support middleware and open standards. Middleware acts like a universal translator, helping different agents and their rules talk easily. This means developers don't need to know every detail, and agents can move smoothly across various systems. How well these rules work together will determine if AI becomes a strong, unified system or a broken collection of digital islands. It's a chance to build something unique.

Your Strategic Advantage on the AI Superhighway

For leaders in technology, understanding MCP, ACP, and A2A is key to shaping organizations. 

These systems promise huge gains in automation, making everyday tasks faster and smarter across all parts of a business. They help AI make better choices by feeding it real-time information. And, they allow for human oversight, so AI works ethically and builds trust. 

But with this new power comes new responsibilities. Strong cybersecurity and implementing proper controls to manage agents are just the beginning. The path ahead might see these protocols merge into a smooth, unified system or split, leading to unexpected challenges. Open standards and shared tools will be important to keep things running seamlessly. 

“This is a generational opportunity for all of us,” Arnold said. “It’s time to create new agentic experiences using innovative technology, tooling, and platform. This is a moment to build something unique.”

It’s time to guide these powerful agents to create a truly connected, efficient, and secure future for everyone. 

Know what over 2,000 global leaders have to say about AI? 98 percent foresee a positive impact for their company. Download the report and discover what AI can do for your team.