AI Governance & Implementation Lead

Role Overview

The AI Governance & Implementation Lead will be responsible for supporting the customer in establishing, operationalising and overseeing AI governance practices at the local level.

The role will work closely with the customer's global/internal AI governance framework and ensure that AI initiatives implemented locally are aligned with organisational policies, governance requirements, risk controls and business objectives.

The resource will also support the assessment and implementation of AI business use cases, providing guidance on whether proposed AI initiatives are justified, appropriately governed and ready for implementation.

Key Responsibilities

AI Governance

• Review and understand the customer's existing internal AI policies, standards and governance framework.
• Establish and maintain the local AI governance operating model in alignment with global/corporate requirements.
• Assess AI initiatives against applicable governance, risk, security, privacy and compliance requirements.
• Define governance checkpoints throughout the AI lifecycle, from use-case identification through implementation and ongoing operation.
• Establish processes for AI use-case submission, assessment, approval, implementation and review.
• Maintain governance documentation, policies, procedures, standards and guidelines.
• Identify potential AI-related risks and recommend appropriate mitigation and controls.
• Ensure appropriate stakeholder involvement for AI initiatives, including Business, IT, Security, Legal, Risk, Compliance and Procurement where required.

AI Use-Case Assessment

• Work with business and technology teams to identify and assess AI opportunities.
• Evaluate proposed AI use cases from business value, feasibility, risk and implementation perspectives.
• Challenge and validate the business justification for proposed AI initiatives.
• Assess whether an AI solution is appropriate for the identified business problem.
• Support prioritisation of AI initiatives based on value, risk, complexity and readiness.
• Develop/maintain AI use-case assessment and approval criteria.