When people talk about AI agent communication, they mean agents communicating with humans. Phone calls to customers. SMS follow-ups. Email outreach.
There's another communication layer that nobody is building and almost nobody is discussing: how agents communicate with each other.
How agent coordination works today
In any multi-agent system — and most production AI deployments are multi-agent, even if they're not designed as such — agents coordinate constantly. An orchestrator calls a subagent. A research agent passes findings to a synthesis agent. A customer-facing agent escalates to a specialist agent. A scheduling agent confirms availability with a calendar agent.
Today, all of this happens through one of two mechanisms:
1. Direct API calls: Agent A calls Agent B's HTTP endpoint. Agent B processes and returns. Simple, but fragile — no shared context, no session state, no audit trail.
2. Shared state stores: Agents read and write to a shared database or message queue. Flexible, but invisible — there's no record of which agent sent which message to which other agent, and no way for a human overseer to follow the interaction.
Both mechanisms share a critical flaw: there's no identity or authentication at the communication layer. When Agent A calls Agent B's endpoint, Agent B has no cryptographic way to verify that the caller is actually Agent A from the expected organization, authorized to request this operation.
Why this matters
As agent systems become more complex and more autonomous, the absence of authenticated agent-to-agent communication creates serious problems:
Auditability: If a customer-facing agent makes a promise that downstream agents act on, where's the record? Which agent made the decision? Which agent authorized the action? Without a communication protocol, the audit trail is reconstructed from logs — fragile and incomplete.
Authorization: An agent claiming to be an orchestrator with elevated permissions is currently indistinguishable from a malicious agent spoofing the orchestrator's identity. There's no protocol-level mechanism to verify "this message actually came from the authorized orchestrator."
Human oversight: Humans who are supposed to oversee agentic workflows often have no visibility into agent-to-agent communication. They see inputs and outputs, but the coordination that happens in between is opaque.
Compliance: If a series of agent-to-agent interactions leads to a communication sent to a human that violates TCPA, which agent bears responsibility? Without a communication audit trail, the answer is "we don't know."
What authenticated agent-to-agent communication looks like
The same ACES primitives that enable agent-to-human communication — ACNs, Agent Attestation Tokens, session management — apply to agent-to-agent communication.
When Agent A (orchestrator) sends a task to Agent B (specialist):
{
"acp_version": "1.0",
"message_id": "msg_a2a_7f3a",
"session_id": "sess_workflow_421",
"from": {
"acn": "acn://getdial.ai/yourco/orchestrator-v2",
"entity_type": "agent",
"signature": "ed25519:..."
},
"to": {
"acn": "acn://getdial.ai/yourco/specialist-legal",
"address_type": "acn"
},
"content": {
"type": "structured",
"body": "Review contract draft for GDPR compliance issues",
"attachments": ["contract_draft_v2.pdf"]
},
"context": {
"thread_id": "thread_contract_882",
"turn_index": 3,
"prior_turns_summary": "Customer requested contract review. Orchestrator drafted initial version."
}
}Agent B receives this message with the orchestrator's cryptographic signature. It can verify against the ACN registry that this message actually came from the authorized orchestrator ACN. If the signature doesn't match, it rejects the message.
The interaction is logged in the session store. The human overseer has a complete, auditable record of what each agent sent to which other agent, in what context.
The oversight question
As agent autonomy increases, human oversight becomes simultaneously more important and more difficult. More important because the consequences of agent errors scale with autonomy. More difficult because the number of interactions between agents grows faster than any human can monitor.
The answer is not less autonomy. It's better observability.
A2A authenticated communication is the foundation of agentic observability. When every agent-to-agent interaction is logged, signed, and session-tracked, human overseers can query the audit trail rather than reconstructing it from logs. They can see at what point in a workflow a decision was made and which agent made it.
The missing channel
Every other agent communication channel is being built: voice, SMS, email, WhatsApp. The industry is racing to give agents better ways to reach humans.
The A2A channel — agents reaching each other — is being ignored, because today's agent communication happens through ad-hoc API calls that nobody thinks of as "communication" requiring a protocol.
But as agent systems grow in complexity and autonomy, the absence of a proper A2A communication protocol will become the most expensive gap in the stack. The infrastructure for it needs to be built now, not as an afterthought.