Role Purpose
The AI Governance Operations & Enablement role enables the effective and scalable execution of the organisation's AI governance framework. This role ensures that AI governance processes, tooling, and documentation are operationalised, consistently applied, and well understood across the enterprise, supporting responsible AI adoption through strong operational discipline and stakeholder enablement.
The AI Governance Operations & Enablement function acts as the backbone of AI governance by maintaining core governance artefacts, operating governance workflows, and providing practical tools and guidance to teams developing or using AI. The role focuses on operational efficiency, transparency, and adoption by managing the enterprise AI use-case inventory, automating governance workflows, and developing standardised templates, SOPs, and playbooks.
In addition, this role drives training and awareness initiatives to build organisational capability and ensure stakeholders understand their responsibilities under the AI governance framework
Responsibilities
- Maintain an enterprise-wide AI use-case inventory, including ownership, risk classification, and lifecycle status
- Operate and continuously improve AI governance workflows covering use-case intake, risk assessment, approval, monitoring, and review
- Support workflow automation using governance, GRC, or internal tooling to improve efficiency and traceability
- Develop and maintain AI governance templates, SOPs, standards, and playbooks
- Ensure governance documentation is complete, current, and audit-ready
- Drive AI governance training and awareness for technical, business, and leadership audiences
- Act as a central coordination point between business, data, risk, legal, and IT teams
Required Knowledge & Skills
- Strong understanding of end-to-end AI/ML model development lifecycle, including problem framing, data preparation, feature engineering, model training, evaluation, deployment, and monitoring
- Strong understanding of AI governance operating models and lifecycle controls
- Experience managing inventories or registries (AI use cases, models, systems, or risks)
- Ability to design structured workflows and control checkpoints
- Excellent documentation and process design skills
- Familiarity with governance tooling, GRC platforms, or workflow automation systems
- Ability to translate governance requirements into practical, usable processes
- Experience designing and delivering training, briefings, or awareness sessions
- Strong stakeholder management and facilitation skills
Experience
- 37+ years of experience in AI governance, technology risk, data governance, PMO, or operational enablement
- Experience supporting governance processes in large or regulated organizations preferred
- Exposure to AI lifecycle management or model operations is an advantage
