Governance

An organization is looking for an experienced professional to further develop and implement its AI Governance framework. Artificial intelligence is playing an increasingly important role, and with it, the impact, risks, and regulatory requirements surrounding AI are increasing. The organization has already established the initial foundations, including a governance model, AI risk classification, and controls.

The focus now is to take this foundation to the next level and ensure that AI Governance is practical, scalable, and embedded within the organization. Importantly, AI Governance should be integrated with existing Data Governance, Privacy, Security, Risk, Compliance, and Enterprise Architecture processes and responsibilities, without creating a separate governance structure.

What you will do.

• Develop the AI Governance Target Operating Model:
• Define the desired end state for AI Governance.
• Define roles, responsibilities, ownership, and decision-making structures.
• Establish governance and controls based on AI risk classifications.
• Determine which responsibilities should sit centrally and which should be embedded within domains, product teams, and platform teams.
• Develop a pragmatic and scalable model that can evolve with AI and the organization.
• Connect AI Governance with Existing Governance:
• Develop a roadmap from the current state to the target operating model.
• Define milestones, priorities, and organizational requirements.
• Advise on the required expertise, capabilities, and organizational structure within Data & AI Governance.
• Ensure alignment with Data Governance, Privacy, Security, Risk, Compliance, Enterprise Architecture, and the AI Centre of Excellence.
• Build support among relevant governance bodies.
• Avoid unnecessary duplication, conflicting decision-making, and excessive governance overhead.
• Implement AI Governance (hands-on role):
• Develop and implement AI risk classification and associated controls.
• Establish assessment, decision-making, and escalation processes.
• Further develop and embed the central AI Registry.
• Translate governance requirements into practical guidelines and processes for product, data, and technology teams.
• Build adoption and support across product teams and Data & AI.
• Establish the foundation for continued adoption and professionalization.
• Drive Adoption and Embedding:
• Develop reporting on AI risks, AI use cases, and overall AI health for leadership and governance boards.
• Advise management and stakeholders on AI Governance, relevant legislation, and next steps.
• Establish clear ownership and accountability.
• Create a roadmap for the continued maturity of AI Governance within the organization.

What they ask

• Proven experience in AI Governance, Responsible AI, or similar governance disciplines.
• Experience designing and implementing governance frameworks and Target Operating Models in complex organizations.
• Strong experience with Data Governance, risk management, controls, and decision-making.
• Strong knowledge of AI, Generative AI, and Agentic AI.
• Good knowledge of relevant legislation and regulations, particularly the EU AI Act.
• Strong stakeholder management and organizational change experience.
• Ability to translate complex governance requirements into practical processes for management, product teams, data professionals, and technology teams.
• Strong preference will be given to candidates who have previously held an AI Governance role or led an AI Governance transformation within one or more complex organizations.
• This is not primarily an advisory role. The candidate must demonstrate experience in determining how governance is actually organized, implemented, and embedded into day-to-day operations.