How to Write an AI Policy

Summary

This practical guide from Tandem breaks down the complex process of creating organizational AI policies into manageable steps. Rather than offering generic policy templates, it focuses on the structural and governance considerations that make AI policies actually work—from establishing the right committees to managing AI vendors effectively. The resource is particularly valuable for its nuanced approach to scaling governance structures based on organizational size and complexity.

What you'll learn

The guide walks through the foundational elements of AI policy development, starting with governance structure design. You'll discover how to assemble cross-functional AI governance committees that bring together IT, security, compliance, and legal teams effectively. The resource provides specific guidance on tailoring your approach based on whether you're a startup with limited resources or a large enterprise with complex regulatory requirements.

A significant portion focuses on vendor management programs—a critical but often overlooked aspect of AI governance. The guide explains how to evaluate AI vendors, establish appropriate contracts, and maintain ongoing oversight of third-party AI services. This practical focus sets it apart from more theoretical policy frameworks.

Who this resource is for

• Compliance officers and legal teams tasked with developing organizational AI policies from scratch
• IT and security leaders who need to integrate AI governance into existing technology frameworks
• Risk management professionals looking to understand how AI policies fit into broader enterprise risk strategies
• Small to medium-sized organizations that need practical, scalable approaches rather than enterprise-only solutions
• Consultants and advisors helping clients navigate AI policy development

Getting your governance structure right

The resource emphasizes that effective AI policies start with the right organizational structure, not just written documents. It provides specific recommendations for committee composition based on organizational size—from lean three-person teams in smaller companies to more complex multi-departmental structures in enterprises.

The guide addresses a common challenge: how to involve technical teams without bogging down policy development in implementation details. It offers concrete suggestions for balancing technical expertise with business and legal perspectives in governance committees.

The vendor management angle

Unlike many AI policy guides that focus primarily on internal AI development, this resource dedicates substantial attention to managing external AI vendors. It covers due diligence processes, contract considerations, and ongoing monitoring requirements—reflecting the reality that most organizations rely heavily on third-party AI services.

The vendor management section includes practical checklists and evaluation criteria that organizations can adapt to their specific needs and risk tolerance levels.

What makes this different

This guide stands out for its emphasis on implementation over ideation. Rather than starting with high-level principles, it begins with the practical question of who should be involved in AI governance and how they should work together. The scalable approach means the guidance remains relevant whether you're implementing your first AI policy or refining an existing program.

The resource also acknowledges resource constraints realistically, offering alternatives for organizations that can't implement comprehensive governance programs immediately but need to start somewhere.