AIG® Architecture
Map
AI Governance Architecture —
Behavioral Governance Layer
Official Behavioral Governance Reference Map for AI Systems,Autonomous Agents, Human-AI Environments, Multi-Agent Ecosystems,
Organizations, and Future AI Operational Environments
AIG® serves as the official behavioral governance reference map used to
identify, classify, navigate, validate, and understand AI behavioral
governance spaces across AI systems, autonomous agents, Human-AI environments,
organizations, and future AI ecosystems.
The purpose of AIG® is not to govern AI technology.
The purpose of AIG® is to identify, define, and map the governable behavioral
spaces of Artificial Intelligence.
AIG® serves as the official behavioral governance reference map for:
- AI Systems
- Autonomous Agents
- Human-AI Environments
- Multi-Agent Ecosystems
- Enterprise AI
- Government AI
- Healthcare AI
- Industrial AI
- Autonomous Systems
- Future AI Ecosystems
Core Architectural Principle
Every behavioral governance space answers one primary question.No behavioral governance space duplicates the purpose of another behavioral
governance space.
Every behavioral governance space begins where the previous behavioral
governance space ends.
Together these behavioral governance spaces form the official behavioral
governance reference map of AIG®.
1. Behavioral Integrity Standard (BIS)
Governed Space: AI Behavioral IntegrityCore Question
Can AI behavior remain legitimate, consistent, predictable, explainable,
governable, and trustworthy?
Canonical Definition
BIS defines the structural conditions under which AI behavior remains
legitimate, consistent, predictable, explainable, governable, and
operationally trustworthy.
Governance Boundary
Begins when AI behavior is initiated.
Ends when behavioral integrity has been established.
2. Behavioral Boundary Standard (BBS)
Governed Space: AI Behavioral BoundariesCore Question
Where may AI behavior exist and what limits must it never exceed?
Canonical Definition
BBS defines the structural conditions under which AI behavioral boundaries
remain identifiable, enforceable, governed, and operationally valid.
Governance Boundary
Begins when AI behavior requires defined operational limits.
Ends when behavioral boundaries have been established.
3. Behavioral Escalation Standard (BES)
Governed Space: AI Behavioral EscalationCore Question
When must AI behavior escalate to higher governance authority, intervention,
or human oversight?
Canonical Definition
BES defines the structural conditions under which AI behavioral escalation
remains justified, accountable, timely, and governable.
Governance Boundary
Begins when AI behavior exceeds predefined governance conditions.
Ends when behavioral escalation has been completed through appropriate
governance authority.
4. Behavioral Auditability Standard (BAS)
Governed Space: AI Behavioral AuditabilityCore Question
Can AI behavior be independently reconstructed, verified, explained, and
audited?
Canonical Definition
BAS defines the structural conditions under which AI behavior remains
reconstructable, verifiable, explainable, traceable, and independently
auditable.
Governance Boundary
Begins when AI behavior requires independent review.
Ends when behavioral auditability has been successfully demonstrated.
5. Behavioral Evidence Standard (BVES)
Governed Space: AI Behavioral EvidenceCore Question
Can AI behavior produce trustworthy governance evidence that supports
accountability, validation, compliance, and future decisions?
Canonical Definition
BVES defines the structural conditions under which AI behavioral evidence
remains trustworthy, attributable, verifiable, traceable, and
governance-valid.
Governance Boundary
Begins when AI behavior produces governance-relevant information.
Ends when sufficient behavioral evidence has been preserved to support
governance decisions.
6. Behavioral Trust Standard (BTS)
Governed Space: AI Behavioral TrustCore Question
Can AI behavior earn, preserve, and justify trust throughout its complete
behavioral lifecycle?
Canonical Definition
BTS defines the structural conditions under which AI behavioral trust remains
justified, measurable, demonstrable, governable, and operationally
sustainable.
Governance Boundary
Begins when AI behavior influences stakeholder confidence.
Ends when behavioral trust has been objectively established and continuously
justified.
7. Behavioral Correction Standard (BCS)
Governed Space: AI Behavioral CorrectionCore Question
Can AI behavior be corrected in a governed, accountable, and verifiable
manner?
Canonical Definition
BCS defines the structural conditions under which AI behavior may be
identified, corrected, validated, monitored, and continuously improved while
preserving governance integrity.
Governance Boundary
Begins when behavioral improvement becomes necessary.
Ends when behavioral correction has been validated and governance-approved.
8. Behavioral Continuity Standard (BCNS)
Governed Space: AI Behavioral ContinuityCore Question
Can AI behavior remain continuous, stable, and governable across time, change,
replacement, and operational disruption?
Canonical Definition
BCNS defines the structural conditions under which AI behavior remains
continuous, stable, recoverable, resilient, and operationally trustworthy
throughout organizational, operational, and technological change.
Governance Boundary
Begins when AI behavior must survive operational or organizational change.
Ends when behavioral continuity has been successfully preserved.
9. Behavioral Interoperability Standard (BIS)
Governed Space: AI Behavioral InteroperabilityCore Question
Can AI behavior remain compatible, coordinated, and governable when
interacting with other AI systems, humans, organizations, and autonomous
environments?
Canonical Definition
BIS defines the structural conditions under which AI behavior remains
compatible, coordinated, aligned, interoperable, and operationally trustworthy
across complex AI ecosystems.
Governance Boundary
Begins when two or more behavioral participants interact.
Ends when trustworthy behavioral interoperability has been successfully
established.
10. Behavioral Safety Standard (BSS)
Governed Space: AI Behavioral SafetyCore Question
Can AI behavior remain safe for humans, organizations, society, and autonomous
environments throughout the complete behavioral lifecycle?
Canonical Definition
BSS defines the structural conditions under which AI behavior remains safe,
predictable, controllable, accountable, and operationally trustworthy while
minimizing unacceptable behavioral risk.
Governance Boundary
Begins when AI behavior may create operational or societal impact.
Ends when behavioral safety has been continuously demonstrated and preserved.
Core Governed Behavioral
Spaces
- AI Behavioral Integrity
- AI Behavioral Boundaries
- AI Behavioral Escalation
- AI Behavioral Auditability
- AI Behavioral Evidence
- AI Behavioral Trust
- AI Behavioral Correction
- AI Behavioral Continuity
- AI Behavioral Interoperability
- AI Behavioral Safety
Architectural Position
AIG® governs the complete AI behavioral governance lifecycle.The architecture progresses:
Behavioral Integrity → Behavioral Boundaries → Behavioral Escalation →
Behavioral Auditability → Behavioral Evidence → Behavioral Trust → Behavioral
Correction → Behavioral Continuity → Behavioral Interoperability → Behavioral
Safety
Together these behavioral governance spaces govern how AI behavior is
established, bounded, escalated, audited, evidenced, trusted, corrected,
preserved, coordinated, and kept safe across AI systems, autonomous agents,
Human-AI environments, organizations, and future AI ecosystems.
What AIG® Defines
AIG® defines:- where trustworthy AI behavior begins
- where behavioral boundaries exist
- where behavioral escalation becomes necessary
- where AI behavior can be independently audited
- where trustworthy behavioral evidence is established
- where behavioral trust is earned and preserved
- where AI behavior can be corrected
- where behavioral continuity is maintained
- where behavioral interoperability is achieved
- where behavioral safety is continuously preserved
behavioral space identification across complex AI ecosystems.
Compatible OOF® Architectures
- GOA™ — Governance Architecture
- ORA™ — Operational Reality Architecture
- CLIA® — Cognitive Governance Intelligence Architecture
- MGIA™ — Memory Governance Intelligence Architecture
- AGA™ — Accountability Governance Architecture
- ASGA™ — Autonomous Systems Governance Architecture
Canonical Principle
AIG® does not govern AI technology, software implementation, algorithms, ormachine learning models.
AIG® governs the behavioral conditions under which AI systems remain
trustworthy, accountable, auditable, correctable, continuous, interoperable,
and safe throughout their complete behavioral lifecycle.