How AI Agents Will Talk to Each Other: The Vocabulary of Agentic AI

By Brian Charles, PhD MBA & Raghu Bala , Founder at Synergetics.ai

AI Is Learning to Talk — But What Language Will It Speak?

We take for granted that humans know how to talk to each other. Whether you’re ordering coffee, negotiating a business deal, or chatting with a friend, there’s an unspoken agreement about words, meaning, and context.

Now imagine a world where AI agents must do the same—but without centuries of cultural evolution to guide them.

In the future, your car won’t just drive itself. It will talk to toll booths, parking meters, and fast-food kiosks. Your AI assistant won’t just schedule meetings—it will negotiate pricing with suppliers and verify inventory with warehouses. AI agents will transact, collaborate, and communicate in ways we can’t yet fully predict.

But for that to happen, they need a common language.

Welcome to the vocabulary of agentic AI.

Why AI Needs a Defined Vocabulary

AI already communicates with humans and other systems. But here’s the problem:

• AI chatbots today rely on natural language processing (NLP), which can be ambiguous.

• API-based systems require hardcoded rules, which don’t scale well.

• There is no universal standard for how AI agents talk to each other.

For agentic AI to work at scale, it needs a structured, extensible way to communicate—one that allows agents to:

✅ Authenticate each other before exchanging data (Know Your Agent - KYA)

✅ Recognize and adopt domain-specific vocabularies

✅ Distinguish transactional vs. informational exchanges

In short, AI needs a structured communication framework—a set of vocabularies that define what an agent knows, how it communicates, and what it can do.

The Two Steps of AI Communication

1️⃣ Authentication: Know Your Agent (KYA)

Before AI agents interact, they must verify each other’s identity and legitimacy. This prevents fraud, misinformation, and rogue agents.

Much like how websites use SSL certificates to prove authenticity, AI agents will rely on Know Your Agent (KYA) protocols to verify:

🔹 Who created the agent

🔹 What organization it belongs to

🔹 What it is authorized to do

This step ensures that agents are trusted entities before they start exchanging information or completing transactions.

2️⃣ The Vocabulary Exchange: What Are We Talking About?

Once authentication is complete, AI agents must determine what “language” they will speak.

Think about it like this:

🚗 A self-driving car talking to a parking meter uses a “parking vocabulary.”

🍔 A car ordering food from a drive-thru AI assistant uses a “fast-food vocabulary.”

💳 A toll booth processing payments uses a “toll system vocabulary.”

Each of these domains requires a structured vocabulary so that AI agents understand each other without ambiguity.

At Synergetics.ai, our patented protocol ensures that AI agents can declare and adopt vocabularies dynamically—just like web browsers support different MIME types (text, image, video, etc.).

How Vocabularies Work in Agentic AI

For AI agents to communicate effectively, they must advertise what vocabularies they understand and support extensible, evolving language structures.

🔹 Baseline Vocabularies (Predefined & Universal) – Out-of-the-box vocabularies for common AI interactions (e.g., payments, logistics, customer service).

🔹 Domain-Specific Vocabularies (Industry-Specific) – AI agents can specialize in certain domains (e.g., healthcare, finance, automotive).

🔹 Extensible Vocabularies (User-Created & Evolving) – New vocabularies can be added over time as industries develop new AI capabilities.

When an agent registers itself in an agent registry (like the one created by Synergetics.ai), it declares which vocabularies it understands.

✅ A vending machine registers itself with a “vending vocabulary.”

✅ A smart traffic light registers with a “traffic control vocabulary.”

✅ A logistics AI registers with a “supply chain vocabulary.”

By structuring AI communication this way, we reduce ambiguity, increase interoperability, and create a scalable framework for AI interaction.

Structured vs. Unstructured AI Communication: The Tradeoff

Some might argue: Why do we need structured vocabularies? Can’t AI just use natural language?

The answer: It depends.

🗣 Natural language is great for human-AI interaction (e.g., chatbots, voice assistants). But it’s slow, ambiguous, and inefficient for AI-to-AI transactions.

💾 Structured vocabularies allow AI agents to communicate with precision and speed.

• Example: An AI ordering food in a drive-thru could say:

• 🗣 Natural language: “I’d like a cheeseburger, a medium fries, and a large drink.”

• 💾 Structured vocabulary: {menu: cheeseburger, size: medium, drink: large}

Structured vocabularies eliminate misunderstandings, speed up transactions, and create a reliable framework for AI interactions.

Why This Matters for Enterprises & AI Builders

If you’re building AI systems, you need to think beyond today’s simple chatbot interactions.

AI is evolving into a network of autonomous agents, and they must be able to communicate seamlessly.

🔹 Without authentication (KYA), AI becomes untrustworthy.

🔹 Without structured vocabularies, AI becomes inefficient.

🔹 Without extensible vocabularies, AI becomes outdated.

At Synergetics.ai, we are developing the foundational protocols for agentic AI communication—so AI agents can talk, transact, and evolve.

🚀 Are you ready to build AI that speaks the language of the future? Let’s talk.

#AI #AgenticAI #AICommunication #SynergeticsAI #SmartAI