ArtData™ Module
AD-AC — ArtData™ Agent Communication Module
ArtData™ Standard System
Module ID: AD-AC
Standard System: ArtData™
Category: AI & Data Integrity Standards (AI)
Subcategory: Agent Communication Integrity
Version: 1.0
Status: Canonical · Module
Compatibility: ArtData™ Standard · MTVF™ · AI Governance Frameworks
Canonical Language: English
About the Module
What the Agent Communication Module Is
The ArtData™ Agent Communication Module (AD-AC) defines structuraltransparency conditions for messages exchanged between AI systems.
As agents increasingly interact with other agents, services, and automated
decision systems, communication integrity becomes critical.
Without structural controls, systems cannot reliably determine message origin,
sender identity, message integrity, or decision responsibility.
AD-AC sets minimum requirements so AI-generated messages stay traceable and accountable.
What This Module Changes
In many AI environments automated messages are exchanged without clear sender identity.This creates risks such as:
- automated misinformation propagation
- loss of accountability
- unreliable decision chains
- compromised system trust
every AI-to-AI message must contain a verifiable origin reference.
Scope
The Agent Communication Module applies to automated communication between:
- AI agents
- machine learning services
- automated decision systems
- API-based AI services
- autonomous system networks
Structural Requirements
To satisfy ArtData™ Agent Communication conditions, the following must be established.Sender Identification
Each automated message must identify the sending system.Minimum requirement:
- system identifier
- service reference or agent ID
Message Integrity Reference
Messages must include an integrity verification reference.Examples:
- message hash
- digital signature
- verification token
Timestamp
Each automated message must include a time reference.Minimum requirement:
- message timestamp
- system time reference
Responsible Entity Declaration
A responsible organization must be identifiable.Minimum requirement:
- organization name
- system operator reference
Minimum Implementation Framework (MIF)
Implementation Steps
Step 1 — Assign Agent Identifier
Each AI system must possess a unique identifier.Examples:
- agent ID
- system reference
- service identifier
Step 2 — Attach Message Timestamp
Every automated message must include a timestamp.This allows communication events to be reconstructed.
Step 3 — Apply Message Integrity Reference
Attach a verification reference to each message.Examples:
- message hash
- digital signature
- verification token
Step 4 — Declare Responsible Entity
The organization operating the AI system must be identifiable.Minimum information:
- organization name
- system operator reference
Use Case 1
Autonomous AI Agent NetworksA company deploys multiple AI agents coordinating logistics operations.
Without communication integrity controls, it is difficult to determine which
agent initiated a decision.
Using the Agent Communication Module:
- each agent has a unique identifier
- every message contains a timestamp
- communication integrity references are attached
- automated decision chains become traceable
- system debugging becomes possible
- operational accountability increases
Use Case 2
AI Service API CommunicationAn AI service communicates with external AI platforms through APIs.
Without communication integrity, messages may be modified or misattributed.
Using the Agent Communication Module:
- sender system identity is attached
- message integrity references are applied
- responsibility is traceable
- AI communication becomes verifiable
- service interactions become more reliable
- trust between automated systems increases