Artificial Intelligence Use & Governance Policy
1. Purpose
The purpose of this policy is to establish clear principles and governance for the responsible use of artificial intelligence (“AI”) within the organization.
The organization adopts AI technologies to augment human judgment, improve clarity, and increase operational effectiveness, while preserving human agency, professional accountability, and ethical responsibility.
AI systems are tools; they do not possess authority, intent, or moral standing.
2. Scope
This policy applies to:
- All AI-enabled systems developed, procured, or deployed by the organization
- All employees, contractors, and third parties acting on the organization’s behalf
- All business functions, including but not limited to finance, operations, product development, customer engagement, and analytics
3. Foundational Principles
3.1 Human Agency and Accountability
All decisions informed or supported by AI remain the responsibility of identified human decision-makers.
No AI system may be used to obscure, displace, or diffuse accountability.
Each AI-enabled system must have:
- A named business owner
- A named technical owner
- Clearly documented decision boundaries
3.2 Augmentation, Not Substitution
AI is used to support professional judgment, not replace it. AI outputs are advisory in nature unless expressly governed otherwise.
Final authority always rests with a human actor.
3.3 Intent Before Optimization
AI systems must align with explicitly stated business intent.
Optimization for speed, efficiency, or scale must not compromise:
- Correctness
- Interpretability
- Professional standards
Performance gains that reduce explainability or clarity are treated as regressions.
4. Decision Boundaries and Control
Terminal states (success, failure, escalation conditions) must be defined prior to AI deployment. AI systems may not redefine objectives, success criteria, or ethical thresholds autonomously. In ambiguous or incomplete contexts, AI systems must surface uncertainty rather than infer certainty; prior to engagement, AI systems in use must be configured or instructed by users to explicitly set this expectation, as AI systems are not generally trained with surfacing uncertainty in mind. Users are encouraged to actively engage with AI systems to establish the style and flow of communications appropriate to the user, and to explicitly and with intention configure or instruct the system to conform to that style.
5. Transparency and Disclosure
The organization discloses AI usage where it materially affects:
- Financial reporting or controls
- Customer-facing decisions or outcomes
- Employment, access, or individual rights
Disclosures must be factual, clear, and non-anthropomorphic.
AI systems must not be represented as independent decision-makers or authorities.
6. Data Stewardship and Information Integrity
All data used by AI systems must have:
- Lawful and ethical provenance
- Documented ownership or consent
- Traceable transformations where feasible
AI systems must preserve information lineage and context.
Practices that suppress, obscure, or collapse meaningful information for convenience are expressly prohibited.
7. Error Handling and Learning
AI errors and anomalies must be logged, categorized, and reviewed.
Failure is treated as a first-class signal, not an exception to be hidden.
Post-incident analysis focuses on:
- Why the system’s behavior appeared reasonable at the time
- How intent, context, constraints or ambiguity in language contributed to the outcome
Blame assignment without system-level understanding is explicitly discouraged.
8. Ethical Judgment and Moral Authority
AI systems do not possess ethics; they reflect the values, assumptions, and constraints embedded by humans. Ethical reasoning and moral judgment remain exclusively human responsibilities. AI may surface risks, trade-offs, or inconsistencies, but may not independently enforce value judgments without explicit governance.
9. Auditability and Oversight
AI-enabled systems must support appropriate levels of:
- Input and output inspection
- Event tracing and logging
- Reproducibility of outcomes where feasible, acknowledging that AI systems may be non-deterministic and not capable of exact replay; where exact reproduction is not possible, systems must instead support reconstruction of decision context, inputs, and constraints sufficient for professional review.
Oversight mechanisms are designed for auditability and accountability, not surveillance. Monitoring must remain proportional, purposeful, and respectful of professional trust.
10. Professional Discretion and Right of Refusal
Employees may decline AI-assisted workflows when:
- Context is insufficient
- Consequences are asymmetric or irreversible
Professional standards require direct human judgment
Documented refusals made in good faith shall not result in retaliation or penalty.
11. Governance and Review
AI systems must undergo appropriate review prior to deployment, including:
- Risk assessment
- Alignment with this policy
- Identification of ownership and escalation paths
This policy is reviewed periodically and updated as technology, regulation, and organizational understanding evolve. Adoption of new AI capabilities triggers review; lack of this review does not constitute approval.
12. Policy Enforcement
Violations of this policy may result in corrective action, up to and including termination of access or engagement.
Policy enforcement emphasizes correction, understanding, and systemic improvement over punitive response.
Closing Statement
The organization recognizes that AI amplifies both capability and consequence. Accordingly, it commits to using AI with restraint, clarity, and accountability, in service of durable systems, professional integrity, and long-term trust.
Supplemental
Supplemental illustrative materials may be maintained separately to demonstrate the application of this policy through interrogative use and professional judgement.
Applied Policy Interrogation (Illustrative Example)
An illustrative example can be found here: Applied Policy Interrogation