AIOGF‑SD‑9.2.2 — AI‑Independent Fallback Paths
Document Identifier: AIOGF‑SD‑9.2.2
Related Control: 9.2.2
Framework: AI Operational Governance Framework (AIOGF)
Author: Randy Manthey
Version: 1.6
Date: March 24, 2026
Status: Working Draft
© 2025–2026 Randy Manthey. All Rights Reserved.
Licensing & Usage Notice (Template v1.6)
[Same as template]
9.2.2.1 Purpose of the Practice
The purpose of this practice is to ensure that recovery remains possible even when AI systems are unavailable, degraded, or unsafe to use.
AI‑independent fallback paths provide a human‑operable, deterministic method of restoring critical systems.
9.2.2.2 Scope & Applicability
This practice applies to:
- all critical recovery workflows
- identity restoration
- infrastructure provisioning
- configuration repair
- cross‑AI dependency breakpoints
9.2.2.3 Recommended Practice Statement
Organizations must define and validate AI‑independent fallback paths for all critical recovery actions.
9.2.2.4 Rationale
AI systems may be:
- offline
- corrupted
- misconfigured
- unable to authenticate
- contributing to the outage
Fallback paths ensure recovery remains possible under all conditions.
Foundational Principle
Recovery must never depend solely on AI systems.
9.2.2.5 Implementation Guidance
Organizations should:
- Identify all recovery steps requiring AI
- Define human‑operable alternatives
- Validate fallback paths regularly
- Ensure documentation is accessible during outages
- Train operators on manual recovery
9.2.2.5.1 Preconditions
- documented recovery procedures
- access to identity and credentials
- offline documentation availability
9.2.2.5.2 Scope & Impact Analysis
Evaluate:
- which systems require manual recovery
- which dependencies must be bypassed
- which AI systems cannot be trusted during outages
9.2.2.5.3 Standards Alignment
Aligns with:
- continuity planning
- disaster recovery
- separation of duties
9.2.2.5.4 Trust Relationship Evaluation
Evaluate:
- whether fallback paths bypass identity controls
- whether manual recovery introduces new risks
9.2.2.5.5 Privilege Escalation Assessment
Assess:
- whether fallback paths grant excessive privileges
9.2.2.5.6 Automated Validation
Automated systems should:
- detect when fallback paths are required
- validate manual recovery readiness
9.2.2.5.7 Human Review Requirements
Human review is required for:
- fallback path approval
- manual recovery execution
9.2.2.5.8 Downstream Impact Analysis
Evaluate:
- impact on automation
- impact on identity
- impact on cross‑AI workflows
9.2.2.5.9 Documentation Requirements
Document:
- fallback procedures
- validation results
- recovery outcomes
9.2.2.6 Business Impact
Failure to define fallback paths may result in:
- unrecoverable outages
- dependency on unavailable AI systems
- extended downtime
9.2.2.7 Expected Outcomes
Organizations should expect:
- predictable manual recovery
- reduced dependency on AI
- improved resilience
9.2.2.8 Examples
Example 1 — Manual Identity Restoration
AI cannot restore identity policies.
Fallback path uses human‑controlled identity recovery.
Example 2 — Manual Infrastructure Provisioning
AI‑based provisioning is offline.
Operators provision infrastructure manually.
9.2.2.9 Alignment to External Frameworks
NIST AI RMF — Govern (partial)
ISO/IEC 42001 — Operational Control (extension)
9.2.2.10 Notes
Fallback paths must be validated regularly.
9.2.2.11 Cross‑References
Internal AI-OGF Controls:
- 9.2.1 AI‑Dependent Recovery Paths
- 9.2.3 Circular Dependency Breakpoints
This document is part of the AI Operational Governance Framework (AI-OGF) and is protected under the AI-OGF Limited Use License. Official source: https://rmanthey-mantheyco.github.io/ai-ogf/