AI Governance Lead

Role Summary The AI Governance Lead will own the development, implementation, and ongoing evolution of the organisation's global AI governance strategy. This role is accountable for ensuring AI is deployed responsibly, ethically, and in compliance with applicable regulations, while enabling innovation ing as the senior authority on AI risk and governance, the role partners across Legal, Technology, Data, Risk, and Executive Leadership to embed effective controls, drive regulatory alignment, and foster a culture of responsible AI use across the enterprise.

Key Responsibilities 1. Strategic Leadership & Governance Define and drive the enterprise-wide AI governance strategy, ensuring alignment with corporate objectives, risk appetite, and regulatory obligations. Establish and continuously enhance the global AI governance framework, including policies, standards, and responsible AI principles. Provide executive oversight of AI governance structures, ensuring accountability across business units as both developers and users of AI solutions.

Lead governance forums and contribute to executive-level decision-making, including reporting to senior leadership and Board committees. Sponsor and oversee certification initiatives (e.g. ISO/IEC 42001) and ensure sustained compliance.
2. Enterprise Risk Oversight & Advisory Own the AI risk management framework and ensure consistent identification, assessment, and mitigation of AI risks across all markets and business functions. Oversee AI risk and impact assessment processes, including fairness, bias, explainability, and human oversight considerations. Provide strategic guidance to senior stakeholders on complex AI risk issues, balancing regulatory compliance with business objectives. Ensure AI risk is fully integrated into the Enterprise Risk Management framework, with clear governance, reporting, and monitoring mechanisms.

Act as the escalation point for material AI risks, incidents, and ethical concerns.
3. Regulatory Strategy & External Alignment Define the organisation's approach to global AI regulation, ensuring readiness for evolving requirements across key jurisdictions (e.g. EU, UK, US, APAC). Interpret regulatory developments and translate them into scalable, actionable governance requirements. Maintain oversight of compliance obligations and provide strategic input into regulatory engagements, audits, and external assurance activities. Represent the organisation in relevant industry forums, working groups, or regulatory discussions where appropriate.

4. Enablement & Organisational Capability Drive adoption of AI governance practices across the organisation, ensuring they are practical, scalable, and embedded into business processes. Establish a global AI literacy and training strategy, tailored to varying levels of seniority and risk exposure. Promote a strong culture of responsible AI, influencing behaviour across technical, operational, and commercial teams. Lead collaboration across Legal, DPO, Technology, and Data teams to align AI governance with broader data and technology controls.

5. Monitoring, Assurance & Reporting Define enterprise-wide AI governance KPIs, metrics, and reporting frameworks to provide transparency on risk, compliance, and maturity. Oversee the lifecycle governance of AI systems, including inventory management, monitoring, and control effectiveness. Ensure robust monitoring of model performance, bias, explainability, and drift, supported by appropriate tooling and processes. Provide regular reporting and insights to Executive Leadership Team and Audit & Risk Committee.

Lead and support internal and external audit activities relating to AI governance.
6. Operational Oversight & Incident Management Oversee the management of AI-related incidents, complaints, and regulatory issues, ensuring coordinated and timely responses. Ensure appropriate transparency, communication, and safeguards are in place for stakeholders impacted by AI systems. Provide executive oversight of third-party AI risk management, including vendor due diligence and ongoing monitoring. Sponsor the implementation and optimisation of AI governance tooling across the enterprise.

Skills, Knowledge & Experience Expertise Deep knowledge of global AI regulation and governance frameworks (e.g. EU AI Act, ISO/IEC 42001, NIST AI RMF, OECD principles). Strong understanding of data protection laws and their intersection with AI (e.g. GDPR, automated decision-making). Extensive experience with AI risk management methodologies, including bias, fairness, explainability, and model governance. Solid understanding of AI technologies and life cycles, including machine learning and generative AI.

Proven track record operating in complex, global, and highly regulated environments. Industry experience (e.g. recruitment or similar sectors) advantageous. Qualifications Degree in a relevant discipline (e.g. AI, Data, Technology, Risk, Compliance). Professional certifications desirable (e.g. IAPP…