First AI Agents, then MCP and A2A: Must-Know Concepts for the Future of Work

Introduction

💡 As professionals, we need to understand these concepts, their applications, and their implications—whether we work in technical roles or on the business side:

• 🚀 If you're from a non-technical background (managers, leaders, or anyone not writing code), it's crucial to understand how to apply these technologies to internal processes to improve organizational efficiency and to deliver more innovative, value-added solutions to clients.

• 🧠 If you're in a technical role (anyone writing code, in any language), it's becoming essential—especially for those early in their careers—to learn and master these concepts. The CEOs of the most influential companies in this space (OpenAI, Anthropic, Meta, Microsoft) predict that within a year, nearly 100% of code will be written by AI agents. Gaining these skills will be vital to staying competitive.

The Rise of AI Agents 🧩

In early 2024, the concept of AI Agents began gaining traction as the next logical step in using LLMs. Agents were given the ability to use external tools autonomously. This meant they could decide when to rely on a tool or when to respond using their internal knowledge.

The proliferation of AI agents, their ability to interact with each other, store and use both short-term and long-term memory, and incorporate context as input gave rise to the concept of Agentic AI:

Agents that use sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems.

📈 By late 2024, the demand for AI Engineers capable of building these agents surged. Companies recognized that 2025 would be the year to adopt these technologies rapidly—not to gain a competitive edge, but to avoid falling behind.

MCP and A2A: The New Standards 🔌

One month later, on November 25, 2024, Anthropic introduced MCP (Model Context Protocol): a new open standard allowing AI agents to connect with external tools, data sources, and systems. Since then, we've seen a rapid growth of MCP-compatible servers and clients that let agents perform actions autonomously using natural language through LLMs.

As if that wasn't enough, just a month ago—on April 9, 2025—Google launched A2A (Agent-to-Agent): a protocol that enables AI agents to communicate securely and coordinate actions across multiple platforms and enterprise systems. This marks a major step toward agent interoperability across teams, providers, and programming languages.

Together, agents + MCP + A2A are accelerating the adoption of AI-based solutions.

What This Means for Professionals 🧑‍💼👨‍💻

Just as we saw six months ago with the rise of AI Agents, companies are now actively looking for professionals who understand and can work with MCP and A2A, not just for technical roles, but also in business, product, and strategic positions, because the organizational innovation and transformation strategies are gradually migrating toward these technologies.

These concepts, alongside others like HITL (Human-in-the-Loop), are already being leveraged by business leaders at global companies to create new value propositions and to redefine internal processes.

Final Thoughts 🧠

Regardless of our background, we must understand our role and apply the right lens: we need to know, learn, and understand how to apply these technologies, assess their impact, and anticipate how they'll affect us. They're reshaping entire business models and industries—fast.

This isn't about getting ahead. It's about not being left behind.

Looking to go further?

Explore the protocols and ideas driving this transformation 🔍📚

What Is Agentic AI? 👉 What is Agentic AI – NVIDIA

Introducing the Model Context Protocol 👉 Model Context Protocol – Anthropic

Get started with the MCP 👉 MCP Official Introduction

Announcing the Agent2Agent Protocol (A2A) 👉 A2A Protocol – Google Developers Blog