AI Policy Template to Guide Organizational AI Governance

Summary

The Responsible AI Institute's AI Policy Template provides organizations with a ready-to-use framework for establishing comprehensive AI governance policies. Rather than starting from scratch, this template offers pre-built policy language covering critical areas like data management, risk assessment, and AI procurement processes. What sets this template apart is its direct integration with the NIST AI Risk Management Framework, translating high-level risk management principles into actionable organizational policies that can be customized and implemented immediately.

What Makes This Template Different

Unlike generic policy frameworks that require extensive interpretation, this template provides specific, actionable policy language that organizations can adapt to their context. The template bridges the gap between regulatory guidance (like the NIST AI RMF) and practical implementation by offering concrete policy statements, procedures, and governance structures. It's designed to be modular, allowing organizations to implement sections incrementally rather than requiring a complete governance overhaul.

The template also addresses the full AI lifecycle within policy language—from initial AI strategy and procurement decisions through deployment, monitoring, and decommissioning. This comprehensive approach means organizations don't need to piece together multiple resources to create cohesive AI governance.

Who This Resource Is For

Primary audience:

• Compliance and risk management teams tasked with developing AI governance policies
• Legal departments needing to translate AI regulations into internal policies
• IT and data governance leaders implementing AI oversight procedures
• Chief AI Officers and AI program managers establishing organizational AI frameworks

Particularly valuable for:

• Mid-to-large enterprises with existing governance structures that need AI-specific policies
• Organizations in regulated industries requiring documented AI risk management
• Companies that have already adopted the NIST AI Risk Management Framework and need implementation guidance
• Businesses facing procurement decisions for AI systems and needing policy guardrails

Getting Started: Implementation Roadmap

Phase 1: Assessment and Customization (Weeks 1-2) Begin by reviewing your organization's existing policy framework and identifying gaps the template can fill. The template is designed to integrate with current governance structures rather than replace them entirely. Customize the policy language to reflect your organization's risk tolerance, industry requirements, and operational context.

Phase 2: Stakeholder Alignment (Weeks 3-4) Use the template's governance structure recommendations to identify key stakeholders and decision-makers. The template includes role definitions and responsibility matrices that can streamline the often-complex process of establishing AI oversight committees and approval workflows.

Phase 3: Pilot Implementation (Weeks 5-8) Rather than implementing all template sections simultaneously, focus on the areas most critical to your current AI initiatives. The data management and risk assessment sections are typically good starting points, as they establish the foundation for other governance activities.

Key Components Breakdown

Risk Management Integration: The template translates NIST AI RMF functions into specific policy requirements, including risk assessment procedures, acceptable risk thresholds, and escalation protocols.

Procurement Governance: Detailed policy language for evaluating AI vendors, conducting due diligence on AI systems, and establishing contractual requirements for AI transparency and accountability.

Data Governance Extensions: AI-specific additions to existing data policies, covering training data quality, bias assessment requirements, and data provenance tracking for AI systems.

Operational Oversight: Policy frameworks for ongoing AI system monitoring, performance evaluation, and incident response specific to AI-related issues.

Watch Out For

The template's comprehensiveness can be overwhelming for organizations with limited AI governance maturity. Resist the temptation to implement everything at once—this often leads to policy frameworks that look good on paper but aren't practically enforceable.

Additionally, while the template provides excellent starting language, it requires customization to be effective. Organizations that adopt the template verbatim without adapting it to their specific context, industry requirements, and risk profile may find gaps in coverage or impractical requirements.

The template assumes a certain level of organizational AI sophistication. Very early-stage organizations or those with limited AI initiatives might find some sections premature for their current needs.