How to Set Up an AI Committee in Your Company’s Governance Framework

Creating an AI committee within a company’s governance framework on the usage of artificial intelligence is no longer a luxury, it is a necessity.

With the rapid development of artificial intelligence and the pressure of regulations like the EU AI Act and the GDPR and the risk of disputes for intellectual property and privacy related breaches, companies cannot delay the setting up of an AI governance framework. And the backbone of such a framework is the AI committee which ensures that innovation goes hand in hand with accountability, that risks are managed effectively, and that legal and ethical standards are embedded in every stage of an AI project.

In this article, I will answer the most pressing questions about how to structure such a body: who should be members, whether a Chief AI Officer is necessary, how the committee should operate and communicate with the rest of the company, how it should interact with GDPR compliance processes, and how its role should be reflected in the company’s AI compliance policy.

Who should be members of the AI committee?

This is the most frequent question we receive lately… An AI committee must be cross-functional by design. Artificial intelligence projects affect technology, data protection, business strategy, and ethics simultaneously. To cover this complexity, the following roles should normally be represented:

• Senior technology leaders such as the CTO, the head of IT or lead data scientists to bring technical knowledge on models, data, and deployment;

• Legal and compliance officers who can interpret regulations like the AI Act, GDPR, consumer protection, and sector-specific rules;

• The Data Protection Officer, whose role is central in ensuring that the handling of personal data in AI projects complies with privacy requirements;

• Cybersecurity or IT security managers, since AI systems are vulnerable to adversarial attacks and require robust infrastructure;

• Risk management specialists, able to frame AI within the broader enterprise risk map, including reputational, financial, and operational risks.

Also, other members such as the head of marketing and the head of HR should be available “on demand” depending on the topic discussed within the AI committee.

The mix of members should be adapted to the company’s size, AI maturity and the sector in which the company operates, but the principle remains: an AI committee must combine multiple perspectives to be effective.

Should there be a Chief AI Officer?

The question of whether to appoint a Chief AI Officer (CAIO) is becoming increasingly relevant. For companies where AI is central to the business model — banks deploying automated credit scoring, health-tech companies relying on diagnostic algorithms, or data driven businesses — the answer is usually yes.

A CAIO can:

• Set a unified AI strategy across the company.

• Act as the permanent chair of the AI committee.

• Ensure alignment between governance, risk, compliance, and business.

• Serve as the key point of contact for regulators, auditors, and external stakeholders.

Where AI is less central, responsibilities can remain spread across existing C-suite functions such as the CTO, CIO, or CDO. However, even in such cases, the AI committee must have clear leadership and accountability to avoid becoming a “talk shop” without enforcement power.

The AI committee shall have in any case a person that is accountable for its operation and is in charge to ensure that it is involved in all the AI related projects of the company which are not approved without the AI committee’s blessing.

How should the AI committee operate and communicate internally?

An AI committee without clear procedures will fail quickly. To work, it needs both authority and communication channels which shall be set up in the company’s AI policy. Good practice includes:

• Charter and mandate: the AI committee must have a written scope and defined responsibilities in relation artificial intelligence systems adopted by the company. This includes reviewing new AI initiatives, setting internal standards, and escalating issues to senior leadership.

• Review, approval, and monitoring of AI systems: the AI committee should be empowered to review, approve, and continuously monitor all artificial intelligence systems developed or adopted by the company. This oversight must follow an “AI by design” approach, ensuring that compliance with the AI Act, the GDPR, intellectual property law, and sector-specific legislation is embedded from the earliest design phase through deployment and monitoring.

• Regular meetings: typically monthly or bi-monthly, with the ability to call extraordinary meetings for high-risk or urgent projects.

• Decision-making: clear rules in indicating that the approval of the AI committee is necessary before the adoption of any artificial intelligence system by the company.

• Departmental liaisons: each department—product, legal, IT, HR, operations—should nominate a contact person to interact with the AI committee to ease its operation.

• Guidelines and training: the AI committee should not only supervise but also provide practical tools, templates, and awareness sessions to embed responsible AI across the organization. If employees do not understand the risks to which the company might be exposed and the procedure to be followed, they will try to by-pass the AI committee.

• Reporting lines: the AI committee should provide periodic reports to the board or a relevant executive committee, summarizing decisions, risks identified, and lessons learned.

This operating model ensures that the AI committee is not isolated but works as a connective tissue between AI projects and company governance.

How shall the AI committee’s operation connect wit the GDPR compliance framework?

The intersection of AI, the relevant committee, and governance is especially visible in the area of data protection. Since most AI systems rely on personal data, GDPR compliance cannot be an afterthought. The AI committee should:

• Ensure that Data Protection Impact Assessments (DPIAs) are performed for high-risk AI systems early in the design phase and perform the Fundamental Rights Impact Assessment (FRIA) when needed under the AI Act.

• Review whether the chosen legal basis for data processing (consent, legitimate interest, contractual necessity) is appropriate.

• Promote privacy by design, including data minimization, anonymization, or pseudonymization when feasible.

• Guarantee that transparency obligations are met: users must know when AI is making decisions about them and must have access to meaningful explanations.

• Oversee integration of data subject rights (access, rectification, erasure, objection) into AI processes.

• Monitor security controls and incident response processes for AI-related data breaches.

These activities shall be coordinated with the DPO to avoid duplications. Indeed, by embedding GDPR into its agenda, the AI committee avoids silos and ensures that data protection requirements are integrated into the broader governance strategy.

How should the AI committee be reflected in the compliance policy?

The last step is formalizing the committee’s role in the company’s AI compliance policy. A policy that does not mention the committee will fail to give it legitimacy and visibility. At a minimum, the policy should:

• Identify the existence of the AI committee, its composition, and its authority.

• Assign responsibilities clearly to members, including the chair or CAIO if appointed.

• Require that certain categories of AI systems—particularly high-risk ones—cannot be deployed without prior review and approval.

• Specify the documentation that must be produced, such as risk assessments, bias audits, and DPIAs.

• Clarify how the committee integrates with GDPR compliance processes.

• Define metrics, monitoring, and reporting obligations.

• Include a clause on periodic review and continuous improvement of both the policy and the committee’s functioning.

This approach ensures that governance is not just aspirational but enforceable, visible, and binding across the company.

Conclusion

An AI committee is the cornerstone of effective corporate governance in the age of artificial intelligence. It brings together diverse expertise, creates a forum for risk management, and provides the oversight necessary to comply with laws like the GDPR, intellectual property law, sector-specific rules, and of course the EU AI Act. By reviewing, approving, and monitoring AI systems with an “AI by design” approach, the committee ensures that compliance is built into innovation, not bolted on afterward.

In a world where trust in AI is as valuable as performance, setting up an AI committee is not only about compliance—it is about building a sustainable competitive advantage.

On a similar topic, you can read the article How Can Your Organization Arrange AI Governance Properly? and our DLA Piper’s AI law journal Diritto Intelligente.