Governance Committees for Generative AI: Roles, RACI, and Cadence

Why Your Company Needs a Generative AI Governance Committee

If your team is using ChatGPT, Claude, or any other generative AI tool to write emails, draft reports, or even handle customer service, you’re already running a risk. Not because the tech is dangerous-but because no one’s in charge. Without a formal governance committee, you’re flying blind. One company in Minnesota lost $1.8 million last year when an AI tool leaked customer PII because no one reviewed the data sources. That wasn’t a hack. It was a governance failure.

By mid-2025, 89% of financial firms and 76% of healthcare organizations had set up AI governance committees. The EU AI Act and U.S. Executive Order 14110 made it a legal expectation, not a best practice. But even if you’re not regulated, you still need a committee. Why? Because generative AI doesn’t just make mistakes-it makes unpredictable mistakes. And without structure, those mistakes become lawsuits, reputational damage, or worse.

Who Belongs on the Committee (And Who Doesn’t)

A good AI governance committee isn’t just a group of executives nodding along. It’s a cross-functional team with real authority and real expertise. The minimum seven roles you need:

• Legal - Knows the EU AI Act, state laws, and contract risks. They’re the ones who say, “This use case violates Article 5.”
• Privacy - Handles data lineage, consent, and anonymization. If your AI was trained on employee emails, they’re the ones who flag it.
• Information Security - Protects against prompt injection, model theft, and data exfiltration. They’ve seen how easily AI can be tricked into spilling secrets.
• Research & Development - Not just engineers, but people who understand fine-tuning, retrieval-augmented generation, and hallucination rates. They translate tech jargon into risk.
• Product Management - Represents the user. They know which AI tools are actually being used and why.
• Ethics & Compliance - Not a PR person. This role asks: “Is this fair? Is this transparent? Who gets hurt if this goes wrong?”
• Executive Leadership - Usually the CTO, CFO, or General Counsel. They have the power to stop a project. If they’re not in the room, the committee is just a suggestion box.

Don’t include HR unless they’ve had AI risk training. Don’t add marketing unless they can explain how bias in a generative model affects customer segmentation. And never let IT run this alone. AI governance isn’t an IT problem-it’s a business problem.

RACI: Who Does What, When

Confusion kills governance. That’s why every committee needs a RACI chart. It’s not optional. Here’s how the top performers use it:

• Accountable - One person. Always the committee chair (usually the CTO or Chief Risk Officer). They sign off on final decisions. No delegation.
• Responsible - Legal owns compliance verification. Security owns system hardening. Privacy owns data validation. Each has clear ownership.
• Consulted - R&D is consulted before any model is deployed. Product is consulted before any customer-facing use case. These are the people who know the details.
• Informed - Business units, frontline teams, and legal departments outside the committee get updates after decisions are made. They don’t vote. They don’t delay.

OneTrust’s data shows companies using RACI reduce approval delays by 47%. Why? Because no one’s guessing who to ask. No one’s waiting for a reply from someone who’s not even on the committee.

Cadence: When to Meet, and How Often

Meetings too often? You become a bottleneck. Too rarely? You miss risks.

Effective committees use a tiered cadence:

1. Executive Committee (Quarterly) - Every 90 days. Reviews policy updates, risk trends, budget, and major use cases. This is where strategic decisions happen.
2. Operational Working Group (Bi-weekly) - Every 14 days. Reviews new AI use cases submitted by teams. Uses a standardized intake form. Decides on risk tiering: low, medium, high.
3. Emergency Review (On-demand) - If a model starts hallucinating in customer chats, or if a vendor changes their terms, the committee can convene within 72 hours using digital voting tools.

At JPMorgan Chase, this structure lets them review 287 AI use cases a year with only 12 rejections. That’s an 85% approval rate-not because they’re lenient, but because they’ve built a system that filters out low-risk ideas fast. High-risk ones? They get deep dives.

The Three Models: Centralized, Federated, Decentralized

Not all governance works the same. Here’s what the market actually uses:

IBM uses centralized. Microsoft uses federated. A small retail chain might try decentralized-but they pay for it later. If your AI is touching customer data, contracts, or compliance-sensitive areas, go centralized or federated. No exceptions.

What Makes a Committee Fail (And How to Avoid It)

Most committees die quietly. They meet once, then stop. Why?

• No veto power - If the committee can’t say “no,” it’s a photo op. Dr. Rumman Chowdhury says 100% of effective committees have veto authority. Period.
• Non-technical members - A marketing VP rejecting an AI tool because “it sounds scary” isn’t governance. It’s fear. You need someone who understands prompt engineering vs. fine-tuning.
• No integration - If your AI governance lives in a separate folder from your data governance or compliance system, it’s a ghost. Successful committees plug into existing risk frameworks.
• No training - Privacera found non-technical members need 20-25 hours of training just to understand hallucinations, bias, and data leakage risks. If you skip this, you’re setting them up to fail.

One company in Chicago had a committee with 11 members. Only two had ever used ChatGPT. They rejected a $2M automation tool because they thought “AI writes everything.” They didn’t know it was just a template engine. Cost? $1.2M in lost opportunity.

Real-World Success: How ODP Corporation Got It Right

The ODP Corporation didn’t start with a fancy tool or a big budget. They started with one question: “What’s the worst thing that could happen if our AI customer service bot gives wrong advice?”

Their Chief Audit Executive joined the committee. Within six months, they found 14 compliance gaps-like AI using unapproved training data from old support tickets. They fixed them before regulators ever asked.

They also built a risk tiering system:

• Low risk - Internal summaries, draft emails. Approved in 5 days.
• Medium risk - Customer-facing chatbots, marketing copy. Requires privacy review. 15-day cycle.
• High risk - Clinical decision support, financial forecasting. Needs legal sign-off, bias testing, and third-party audit. 25-day cycle.

Result? Approval time dropped from 45 days to 12. And they’ve had zero regulatory incidents since.

What’s Coming Next (And How to Prepare)

The SEC will require public companies to disclose their AI governance committee composition by Q3 2025. That’s not a suggestion-it’s a filing requirement. If you’re not ready, you’ll be flagged.

Also, automated monitoring tools are now standard. Leading companies use dashboards that track:

• Model drift (how much output has changed since last update)
• Usage spikes (sudden increase in AI use = potential shadow IT)
• Complaint volume (are users reporting errors?)

These tools don’t replace the committee-they give the committee real-time data. No more guessing. Just facts.

By 2027, 83% of analysts predict routine governance tasks-like risk scoring and documentation updates-will be automated. The committee’s job won’t be to review every prompt. It’ll be to set the guardrails, monitor the outcomes, and respond when things go off-track.

Your Next Steps

If you don’t have a committee yet:

1. Identify your top 3 AI use cases right now. Are they customer-facing? Do they use sensitive data?
2. Find the 7 roles listed above. Start with who’s already doing this work-don’t hire new people yet.
3. Write a one-page charter. Define your mission: “To ensure all generative AI use is safe, legal, and aligned with company values.”
4. Set your first meeting. Bi-weekly. Use a simple intake form. Track everything.
5. Train your members. Even 2 hours of basics on hallucinations and bias will make a difference.

Don’t wait for a breach. Don’t wait for a regulator. Start now. Because the next AI failure won’t be an accident. It’ll be a failure of leadership.