ZYNAGI Governance Resources
AI Policy Template for Responsible AI Use
A practical AI policy starter framework covering acceptable use, prohibited use, data protection rules, approval workflows, vendor review, training, and enforcement for enterprise organizations.
Request a Custom AI Policy ReviewTL;DR — Key Takeaways
- An AI policy is the foundational governance document that defines what AI use is permitted, prohibited, and conditional within an organization.
- This template covers seven core sections: acceptable use, prohibited use, PHI and confidential data rules, approval workflows, vendor review, employee training, and monitoring.
- A policy template is a starting point — organizations need custom review to adapt provisions to their industry, regulatory environment, and operational risk profile.
- AI policies must be living documents, reviewed annually and updated when AI capabilities or regulations change.
- Policy without enforcement is documentation, not governance. Effective policies include monitoring, accountability, and consequences for non-compliance.
Executive Summary
An AI policy is the foundational governance document that defines how an organization permits, prohibits, and manages the use of artificial intelligence. Without a policy, AI adoption proceeds without boundaries — employees use AI tools with sensitive data, vendors are adopted without assessment, and governance accountability is undefined.
This page provides a practical AI policy starter framework — not the full platform, but the structural sections that every organization needs to establish governance boundaries. Each section outlines the provisions that a comprehensive AI policy should address, adapted to the organization's industry, regulatory environment, and operational risk profile.
Organizations seeking a fully customized AI policy — adapted to their specific compliance obligations, operational workflows, and risk tolerance — should request a Custom AI Policy Review.
Why an AI Policy Matters
AI adoption without policy creates organizational exposure that is difficult to remediate after the fact. Employees experiment with general-purpose AI tools, departments adopt AI-enabled software without review, and vendors gain access to organizational data without contractual governance — all without defined boundaries or accountability.
An AI policy establishes the rules of the road: what AI use is approved, what is prohibited, what requires approval, how data must be handled, how vendors must be assessed, and what happens when the policy is violated. It is the document that transforms AI governance from intention to operational reality.
Governance Principle
A policy that is written but not distributed, trained, enforced, or monitored provides no governance value. The policy is the starting point — enforcement is the governance.
AI Policy Template Sections
The following seven sections comprise the core structure of a comprehensive AI governance policy. Each section addresses a distinct dimension of organizational AI risk and accountability.
Acceptable AI Use
Defines the AI tools, use cases, and workflows that are approved within the organization.
Approved AI tools list with specific tool names and versions
Approved use cases by department and function
Data types permitted for use with approved AI tools
Required disclosures for AI-assisted work products
Human oversight requirements for AI-assisted decisions
Prohibited AI Use
Explicitly defines AI uses that are not permitted under any circumstances.
General-purpose AI tools with PHI or confidential data
AI tools without vendor assessment and BAA where applicable
AI in clinical decision-making without validation and oversight
AI-generated content for client communication without review
AI tools that retain or train on organizational data without consent
PHI and Confidential Data Rules
Defines how sensitive data may and may not be used with AI systems.
PHI may only enter AI systems with documented BAA coverage
Confidential business data requires executive approval before AI use
Client financial data requires compliance review before AI processing
Employee PII handling rules for AI tools
Data retention and deletion requirements for AI vendors
Approval Workflow
Defines the process for evaluating and authorizing new AI deployments.
New AI deployments require IT and compliance review before adoption
Risk assessment required for AI tools accessing sensitive data
Executive approval required for AI in regulated workflows
Vendor assessment required before AI vendor contracts are signed
Documentation requirements for approved AI deployments
Vendor Review
Defines requirements for evaluating and managing third-party AI vendors.
BAA required for all AI vendors accessing PHI
SOC 2 Type II compliance for vendors handling sensitive data
Data retention, sub-processor, and training practices must be documented
Annual reassessment required for high-risk vendors
Vendor changes must be reported to governance committee
Employee Training
Defines training requirements for staff who use or oversee AI systems.
All staff must complete AI governance training annually
Training covers approved tools, prohibited uses, and data rules
Department-specific training for high-risk AI workflows
Acknowledgment of policy required before AI tool access
New hire AI governance onboarding within 30 days
Monitoring and Enforcement
Defines how policy compliance is monitored and what happens when violations occur.
AI tool usage monitored through inventory and access logs
Vendor compliance monitored through periodic reassessment
Policy violations documented and escalated to governance committee
Disciplinary consequences for policy violations defined
Annual policy review and update process established
Adapting the Template to Your Organization
A template provides structure, not a finished policy. Organizations must adapt each section to their specific industry, regulatory environment, operational risk profile, and organizational culture.
Healthcare Organizations
Healthcare AI policies must address HIPAA compliance, PHI protection in AI workflows, clinical AI accountability, BAA requirements for AI vendors, and multi-location governance for DSOs and health systems. Review the Healthcare AI Governance Framework for healthcare-specific provisions.
Financial Services
Financial advisory AI policies must address fiduciary obligations, SEC compliance, client data protection, AI use in advisory workflows, and regulatory reporting. Review the Financial Services AI Governance Framework for financial services provisions.
Professional Services
Law firms, accounting practices, and consulting organizations must address confidentiality, attorney-client privilege, professional responsibility rules, and AI use in research and client communication.
From Policy to Governance
An AI policy is one component of a comprehensive AI governance framework. The policy defines the rules; the framework provides the infrastructure — inventory, risk scoring, vendor management, monitoring, and audit trails — that makes the rules operational.
Organizations that adopt policies without governance infrastructure find that policy enforcement is inconsistent, monitoring is absent, and governance accountability is diffuse. The AI governance platform provides the infrastructure that makes the policy enforceable.
To understand your current governance posture before developing policy, conduct an AI risk assessment or measure your AI Trust Score. To build the inventory that policy enforcement requires, start with an AI inventory.
Industry Considerations
Healthcare Organizations
AI policies for healthcare must address HIPAA, PHI protection in AI workflows, clinical AI accountability, BAA requirements, and multi-location governance for DSOs and health systems.
Financial Advisory Firms
AI policies for financial services must address fiduciary obligations, SEC compliance, client data protection, AI in advisory workflows, and regulatory reporting requirements.
Law Firms
AI policies for legal organizations must address attorney-client privilege, confidentiality, professional responsibility, and AI use in legal research and document review.
Multi-Location Businesses
AI policies for multi-location operations must address centralized policy enforcement, location-level compliance, and acquisition integration of unassessed AI tools.
Governance Checklist
- Acceptable AI use list defined and documented
- Prohibited AI use explicitly stated in policy
- PHI and confidential data handling rules established
- Approval workflow for new AI deployments documented
- Vendor review requirements defined
- Employee training program designed and scheduled
- Monitoring and enforcement provisions established
- Executive accountability for policy designated
- Annual policy review schedule established
- Policy distributed and acknowledged by all staff
Frequently Asked Questions
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