AIOGF‑SD‑10.2.1 — Independent Hardware

Document Identifier: AIOGF‑SD‑10.2.1
Related Control: 10.2.1
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.

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10.2.1.1 Purpose of the Practice

The purpose of this practice is to ensure that critical AI systems operate on hardware that is physically and logically independent from shared compute, shared control planes, and vendor‑managed infrastructure.

Independent hardware prevents shared failure modes and ensures that AI systems remain operational even when upstream systems fail.

10.2.1.2 Scope & Applicability

This practice applies to:

critical AI systems
autonomous AI systems
AI systems performing security or identity functions
AI systems requiring air‑gapped operation
robotics‑based AI maintenance systems

10.2.1.3 Recommended Practice Statement

Organizations must deploy critical AI systems on hardware that is physically and logically isolated from shared infrastructure and vendor‑controlled environments.

10.2.1.4 Rationale

Shared hardware introduces risks such as:

cascading failures
cross‑tenant interference
vendor outages
shared control plane compromise
inability to maintain air‑gaps

Independent hardware ensures predictable, resilient AI operation.

Foundational Principle

Critical AI systems must operate on hardware that is fully controlled by the organization and isolated from shared failure domains.

10.2.1.5 Implementation Guidance

Organizations should:

Identify AI systems requiring independent hardware
Deploy dedicated compute, storage, and networking
Disable vendor‑controlled management planes
Implement local identity and access controls
Validate isolation through testing

10.2.1.5.1 Preconditions

hardware procurement
isolation requirements
identity and access controls

10.2.1.5.2 Scope & Impact Analysis

Evaluate:

which AI systems require dedicated hardware
which dependencies introduce shared risk
which workloads cannot tolerate vendor outages

10.2.1.5.3 Standards Alignment

Aligns with:

supply chain security
operational continuity
separation of duties

10.2.1.5.4 Trust Relationship Evaluation

Evaluate:

vendor‑controlled firmware
remote management interfaces
cross‑system trust boundaries

10.2.1.5.5 Privilege Escalation Assessment

Assess:

whether shared hardware grants unintended privileges
whether management interfaces can escalate AI capabilities

10.2.1.5.6 Automated Validation

Automated systems should:

detect shared infrastructure
validate hardware isolation
alert when isolation is breached

10.2.1.5.7 Human Review Requirements

Human review is required for:

hardware selection
isolation boundary approval

10.2.1.5.8 Downstream Impact Analysis

Evaluate:

impact on robotics maintenance
impact on update channels
impact on continuity

10.2.1.5.9 Documentation Requirements

Document:

hardware specifications
isolation boundaries
management interface restrictions

10.2.1.6 Business Impact

Failure to deploy independent hardware may result in:

cascading outages
vendor‑controlled failures
compromised isolation
loss of operational independence

10.2.1.7 Expected Outcomes

Organizations should expect:

predictable AI operation
reduced dependency risk
improved continuity

10.2.1.8 Examples

Example 1 — Shared GPU Cluster Failure

A shared GPU cluster fails.
Independent AI hardware remains operational.

10.2.1.9 Alignment to External Frameworks

NIST AI RMF — Manage (extension)
ISO/IEC 42001 — Operational Control (extension)

10.2.1.10 Notes

Independent hardware must be validated regularly.

10.2.1.11 Cross‑References

Internal AI-OGF Controls:

10.2.2 Robotics‑Based Maintenance
10.2.3 Isolated Update Channels

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/