Chief AI Officer / Head of Machine Learning / AI Transformation Executive

Role DescriptionThe Chief AI Officer / Head of Machine Learning / AI Transformation Executive leads an organisation’s artificial-intelligence strategy, machine-learning capabilities, and responsible adoption of AI technologies. This executive role identifies high-value AI opportunities, connects AI investment to business priorities, and builds the governance, talent, platforms, and operating models needed to deliver sustainable impact.The position works closely with executive leadership, Technology, Data, Product, Operations, Risk, Legal, Security, and business teams to define AI roadmaps and oversee delivery. Responsibilities include prioritising use cases, establishing AI and data standards, guiding the development and deployment of machine-learning and generative-AI solutions, managing external technology partners, and ensuring programmes deliver measurable business value.The role also champions responsible AI by establishing controls for privacy, security, fairness, transparency, model risk, and regulatory compliance. It communicates complex AI opportunities and risks clearly to senior stakeholders, develops AI capability across the organisation, and leads transformation initiatives from strategy through implementation and adoption.QualificationsBachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Business, or a related field.Advanced degree in a relevant technical or business discipline is an advantage.Significant leadership experience in artificial intelligence, machine learning, data science, digital transformation, technology strategy, or product innovation.Proven experience developing and executing enterprise AI, data, analytics, or technology-transformation strategies.Strong understanding of machine learning, generative AI, large language models, data platforms, cloud technologies, MLOps, and AI product development.Experience identifying, evaluating, and prioritising AI use cases based on business value, feasibility, risk, and scalability.Ability to lead cross-functional teams spanning data science, engineering, product, operations, security, legal, risk, and business functions.Experience establishing AI governance, responsible-AI principles, model-risk controls, data-privacy practices, and compliance frameworks.Strong understanding of AI lifecycle management, including data preparation, model development, validation, deployment, monitoring, and continuous improvement.Experience managing AI investments, technology vendors, strategic partnerships, budgets, and executive-level business cases.Ability to define success metrics and demonstrate the operational, commercial, customer, or productivity impact of AI initiatives.Excellent executive communication, stakeholder-management, influencing, and change-leadership skills.Strong commercial judgement with the ability to balance innovation, delivery speed, technical risk, ethics, and regulatory obligations.Experience leading AI adoption in large, regulated, international, or technology-driven organisations is an advantage.