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This policy establishes the constitutional rules for artificial intelligence within the organization. It governs two distinct surfaces:
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.
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.
| Capability | A technical fact about what a system can do. |
|---|---|
| Authority | A 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.
| Intended | A human or authorized process has decided the action should occur. |
|---|---|
| Attempted | The system has initiated the action. |
| Completed | The system reports that the action has finished. |
| Verified | Appropriate 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.
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.
The organization maintains deliberate visibility into where and how AI is used. Shadow or unapproved usage is a governance gap requiring remediation.
Before any consequential automated or agentic action:
Human responsibility must be assignable in advance, not discovered after the fact.
Every material AI-assisted decision or action has a named human owner. Authority drift—treating AI outputs as decisions rather than assistance—is prohibited.
Three layers must never be conflated:
| Source Truth | What does the organization actually publish and attest to? |
|---|---|
| AI Representation | What does an AI system currently say or believe about the organization? |
| Organizational Authority | What 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.
The organization periodically examines what major AI systems say about its services, locations, leadership, claims, and reputation. Material inaccuracies are assigned for assessment.
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.
| Executive Leadership | Ultimate accountability for the Marshall Principle and this policy |
|---|---|
| AI Governance Owner | Visibility, agent authorization records, external representation monitoring, policy currency |
| Managers | Boundaries, escalation, human ownership on their teams |
| All personnel | Use AI only within authorized boundaries; never substitute AI for judgment or evidence |
| Communications | Accuracy 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.
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.
Exceptions require written approval from the Policy Owner and must include a documented risk assessment and time-bound justification.
Rule of Hierarchy: Lower layers may implement or constrain the layers above. They may not contradict them.
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.
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.
© 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.