AI Governance Manager

The Role Teneo is seeking an experienced AI Governance Manager to help design, implement, and operationalise the firm’s approach to responsible AI governance and enablement. This role sits at the intersection of AI enablement, information security, data governance, privacy, legal, compliance, risk, and technology. You will help ensure AI use cases across the firm are assessed, governed, documented, monitored, and enabled in a consistent, risk-based, and business-aligned way. The role is weighted toward governance, risk, and control, while also supporting responsible AI adoption through practical guidance, stakeholder education, and clear enablement pathways. You will help teams understand how to use AI safely and effectively, while ensuring the right guardrails, evidence, approvals, and oversight are in place. This role is suited to someone who understands the opportunities and risks associated with AI adoption, particularly generative AI, agentic AI, SaaS AI features, and third-party AI platforms. You do not need to be a hands-on machine learning engineer, but you should be comfortable engaging with technical, risk, and business stakeholders to evaluate AI use cases, identify risks, define controls, and support responsible adoption. You will play a key role in helping Teneo enable innovation while maintaining strong governance, auditability, security, privacy, and client trust. The position is based in London and follows a hybrid working model, with three days per week in the office. Responsibilities AI Governance, Risk & Controls - Primary Focus AI Governance Framework & Controls Support the design, implementation, and continuous improvement of Teneo’s AI governance framework, including policies, standards, procedures, controls, and operating processes. Help define and embed responsible AI principles across the organisation, including transparency, accountability, fairness, privacy, security, human oversight, and appropriate use. Develop practical governance processes that guide AI initiatives from idea to approval, implementation, monitoring, and retirement in a controlled and repeatable way. Align AI governance practices with broader information security, privacy, legal, data governance, third-party risk, and enterprise risk frameworks. Support the development of clear, auditable documentation and control evidence for AI-related decisions, approvals, risks, exceptions, and mitigations. AI Use Case Lifecycle Management Partner with AI enablement, technology, data, legal, privacy, security, and business stakeholders to guide AI use cases through appropriate review and governance pathways. Support intake, triage, assessment, approval, and ongoing review of AI use cases, including generative AI tools, internal AI solutions, third-party AI platforms, and embedded AI capabilities in SaaS products. Ensure AI use cases are evaluated for business value, duplication, data sensitivity, security risk, privacy considerations, model/output risk, operational resilience, and alignment with enterprise standards. Maintain AI inventories, use case registers, attestations, and supporting documentation for approved and production AI solutions. Help define requirements for production readiness, including ownership, monitoring, access controls, data handling, testing, human oversight, and exit or retirement considerations. AI Risk Assessment & Responsible AI Assurance Conduct or support AI risk assessments to identify risks related to data exposure, privacy, bias, explainability, output reliability, intellectual property, security, vendor dependency, and misuse. Work with technical and business stakeholders to define appropriate controls and mitigations based on the risk profile of each AI use case. Support the review of third-party AI tools and platforms, working closely with Third Party Risk, Legal, Privacy, Procurement, and Information Security teams. Ensure AI governance activities produce consistent, traceable, and defensible artefacts to…