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Company AI Governance Policy

Version 1.2 — Constitutional / policy layer
Effective: 15 August 2026
Policy owner: Richard K. Marshall · Marshall Intelligence / Marshall Network Services
Review: annual, or upon material change in AI capability, agent autonomy, or regulation
Plain text: ai-governance.md

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The Marshall Principle
Artificial intelligence may assist human decision-making, but responsibility always remains with humans.

Capability does not confer authority. Final responsibility for every material decision, action, and representation remains with identifiable human decision-makers.

1. Purpose

This policy establishes the constitutional rules for artificial intelligence within the organization. It governs two distinct surfaces:

  1. Internal use — what AI systems and agents are permitted to do inside the organization.
  2. External representation — what external AI systems say about the organization.

The policy is deliberately principle-based and compact. Detailed controls, tool registries, authorization matrices, evidence requirements, audit procedures, and operational playbooks live in the layers beneath it.

2. The Marshall Principle (Constitutional Foundation)

This principle is non-delegable.

Capability does not confer authority. An AI system or agent may be technically capable of performing an action (sending email, modifying a database, publishing content, executing a transaction, or communicating externally). That technical capability does not, by itself, authorize the action. Authority is a human decision that must be explicitly granted.

3. Core Distinctions

3.1 Capability vs. Authority

CapabilityA technical fact about what a system can do.
AuthorityA human decision about what a system is permitted to do.

No AI system or agent acquires authority simply because it possesses credentials, tools, API access, or the technical ability to act.

3.2 Four States of Action

IntendedA human or authorized process has decided the action should occur.
AttemptedThe system has initiated the action.
CompletedThe system reports that the action has finished.
VerifiedAppropriate evidence confirms that the intended outcome actually occurred, at a level of assurance proportionate to materiality.

Claiming an action is “done” when it is only Attempted or Completed (but not Verified to the required degree) is a governance failure.

3.3 Evidence Standard

AI-generated assertions are not evidence merely because an AI system produced them. Material claims must be traceable to appropriate source evidence.

“The AI said so” does not meet the evidence standard.

4. Internal Use of Artificial Intelligence

4.1 Visibility

The organization maintains deliberate visibility into where and how AI is used. Shadow or unapproved usage is a governance gap requiring remediation.

4.2 Boundaries

4.3 Agent Identity and Delegation

Before any consequential automated or agentic action:

Human responsibility must be assignable in advance, not discovered after the fact.

4.4 Accountability

Every material AI-assisted decision or action has a named human owner. Authority drift—treating AI outputs as decisions rather than assistance—is prohibited.

5. External Representation to AI Systems and Agents

Three layers must never be conflated:

Source TruthWhat does the organization actually publish and attest to?
AI RepresentationWhat does an AI system currently say or believe about the organization?
Organizational AuthorityWhat has the organization actually authorized?

An AI system’s representation of the organization is an observation about that AI system. It is not an authoritative representation by the organization.

5.1 Visibility of External Representations

The organization periodically examines what major AI systems say about its services, locations, leadership, claims, and reputation. Material inaccuracies are assigned for assessment.

5.2 Representation vs. Authority

5.3 Accountability

When an AI representation could harm customers, partners, or commercial outcomes, a named human assesses whether corrective action is warranted. Confident AI prose is never authoritative by itself.

6. Roles and Responsibilities

Executive LeadershipUltimate accountability for the Marshall Principle and this policy
AI Governance OwnerVisibility, agent authorization records, external representation monitoring, policy currency
ManagersBoundaries, escalation, human ownership on their teams
All personnelUse AI only within authorized boundaries; never substitute AI for judgment or evidence
CommunicationsAccuracy of public source truth external AI systems draw upon

At Marshall Intelligence, the accountable human principal for production Send and commercial commitments is Richard K. Marshall.

7. Training and Awareness

Relevant personnel receive periodic awareness of this policy, the Marshall Principle, capability vs. authority, the four states of action, the evidence standard, agent delegation, and the three-layer external model. New hires are introduced during onboarding.

8. Exceptions

Exceptions require written approval from the Policy Owner and must include a documented risk assessment and time-bound justification.

9. Architectural Hierarchy

CONSTITUTION ↓ POLICY ↓ GOVERNANCE ↓ CONTROLS ↓ PROCEDURES ↓ OPERATIONS ↓ EVIDENCE ↓ VERIFIED OUTCOME

Rule of Hierarchy: Lower layers may implement or constrain the layers above. They may not contradict them.

10. Governance Invariants

  1. AI may assist.
  2. Responsibility remains human.
  3. Capability ≠ authority.
  4. Authority must be explicitly delegated.
  5. The human principal must exist before consequential action.
  6. Assertions ≠ evidence.
  7. Attempted ≠ completed.
  8. Completed ≠ verified.
  9. AI representation ≠ organizational authority.
  10. Controls implement policy; they do not override it.

11. Enforcement and Continuous Improvement

Violations are handled under existing disciplinary and compliance processes. Gaps in visibility, unclear authority, missing human principals, unverified claims of completion, or conflation of AI representations with organizational authority are treated as opportunities to strengthen governance.

This policy is reviewed at least annually. Conceptual expansion is intentionally resisted; further development belongs in the operational layers beneath it.

Guiding Note

The Marshall Principle remains the fixed point: AI may assist. Responsibility stays human.

Capability never equals authority. Evidence is required. Actions must be capable of verification proportionate to their materiality. External AI representations are observations about AI systems, not statements by the organization.

Everything else is implementation.

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© Marshall Network Services · Lexington, Kentucky
Free public policy document — not legal advice for your organization; it is how we govern AI here.
Internal implementation notes are operational layers under this constitution.