Establishing an AI Governance Committee: An Inside Look at OneTrust's Process

Summary

OneTrust pulls back the curtain on their internal AI governance structure, revealing a practical two-tiered committee model that balances executive oversight with operational agility. This resource breaks down their approach to quarterly executive reviews of AI strategy and policy while empowering smaller working groups to handle frequent use case assessments and policy updates. Rather than theoretical frameworks, this offers battle-tested insights from a company actively managing AI governance at scale.

The Two-Tiered Structure Explained

OneTrust's governance model centers on a strategic division of responsibilities:

Executive Committee (Quarterly Focus):

• Strategic AI direction and investment decisions
• High-level policy approval and updates
• Performance metrics review across all AI initiatives
• Risk tolerance and appetite setting
• Cross-functional alignment on AI priorities

Working Groups (Ongoing Operations):

• Individual AI use case evaluation and monitoring
• Detailed policy implementation and refinement
• Technical risk assessments
• Vendor and tool evaluations
• Day-to-day compliance tracking

This structure prevents executive bottlenecks while ensuring strategic alignment—executive committees aren't bogged down in operational details, while working groups have clear authority to act within established parameters.

Why This Dual-Layer Approach Works

The quarterly executive rhythm addresses a common governance challenge: AI moves too fast for monthly executive reviews but too slow for ad hoc decision-making. OneTrust's model creates predictable decision points while maintaining operational flexibility between cycles.

Working groups handle the continuous stream of AI decisions—new use cases, tool evaluations, policy clarifications—without waiting for executive input. This prevents AI initiatives from stalling while maintaining proper oversight through structured reporting to the executive committee.

What You'll Learn from OneTrust's Experience

• Committee composition strategies: How to balance technical expertise with business leadership
• Meeting cadence optimization: Why quarterly executive reviews paired with more frequent working group sessions create effective governance
• Escalation pathways: Clear criteria for when working group decisions require executive committee input
• Documentation frameworks: How OneTrust structures policy updates and use case assessments
• Success metrics: What performance indicators their executive committee actually reviews

The resource includes specific examples of how OneTrust's committees handle real scenarios—from evaluating new AI vendors to updating data handling policies when new AI applications are deployed.

Who This Resource Is For

Primary audience:

• Chief Privacy Officers and Chief Information Officers establishing formal AI governance
• Compliance teams tasked with creating AI oversight structures
• Legal teams developing AI governance policies and procedures

Also valuable for:

• Risk management professionals seeking proven governance models
• Executive teams considering AI governance committee structures
• Privacy and security teams implementing AI oversight processes
• Organizations moving from informal to formal AI governance

Getting Started with OneTrust's Model

Begin by mapping your current AI decision-making processes against OneTrust's two-tiered structure. Identify decisions that truly require executive input versus those that operational teams can handle with proper guidelines.

Consider piloting the quarterly executive review cycle first—this creates the strategic foundation and policy framework that working groups need to operate effectively. OneTrust's experience suggests starting with fewer, more focused working groups rather than trying to cover every AI use case immediately.

The resource provides specific guidance on committee charters, meeting agendas, and reporting templates that can be adapted to different organizational contexts and sizes.