Head, AI Transformation Office

Job Summary

• The Head of the AI Transformation Office (AITO) leads the enterprise-wide adoption of Artificial Intelligence and Intelligent Automation to accelerate business growth, operational excellence, customer experience, workforce productivity, and innovation.
• The role is accountable for developing and executing the company's AI strategy, establishing responsible AI governance, prioritizing enterprise AI investments, and ensuring that AI initiatives deliver measurable business outcomes. The Head of AITO serves as the central orchestrator of AI transformation across business units, technology teams, and corporate functions.
• This role reports to the Group Head, ICT & Transformation (or equivalent executive sponsor) and works closely with business leaders, digital teams, data teams, risk and compliance functions, and external technology partners.

General Responsibilities

Enterprise AI Strategy and Roadmap

• Develop and maintain the enterprise AI Strategy aligned with corporate objectives.
• Define a multi-year AI transformation roadmap focused on business value creation.
• Identify priority business domains and use cases where AI can generate significant operational, customer, financial, or strategic benefits.
• Establish AI investment priorities and portfolio governance mechanisms.
• Continuously assess emerging AI technologies, industry trends, and market opportunities.

AI Demand Management and Prioritization

• Establish a structured AI demand intake, evaluation, and prioritization process.
• Partner with business units to identify high-value use cases and transformation opportunities.
• Evaluate opportunities based on:
• Strategic alignment
• Financial returns
• Customer impact
• Productivity gains
• Technical feasibility
• Risk profile
• Maintain and govern the enterprise AI portfolio.

Business Transformation and Value Realization

• Lead AI-enabled transformation of critical business processes across the enterprise.
• Ensure AI initiatives focus on measurable outcomes rather than technology experimentation.
• Track and report realization of:
• Revenue enablement
• Cost reduction
• Productivity improvement
• Customer experience enhancement
• Risk reduction
• Establish enterprise AI KPIs and benefit-tracking methodologies.

AI Governance, Risk, and Responsible AI

• Establish enterprise policies, standards, and controls for responsible AI use.
• Ensure compliance with legal, regulatory, cybersecurity, privacy, and ethical AI requirements.
• Chair or co-chair the AI Governance Council.
• Define governance frameworks covering:
• Model management
• Risk assessment
• Data governance
• Security
• Explainability
• Bias management
• Human oversight
• Manage AI-related enterprise risks and mitigation plans.

AI Solutions Delivery and Scaling

• Oversee delivery of AI and intelligent automation initiatives from concept through implementation.
• Ensure scalable, reusable, secure, and maintainable AI solutions.
• Drive standardization of tools, platforms, architectures, and development practices.
• Promote reuse of AI assets across business units.
• Enable transition from pilots and proofs-of-concept to enterprise-scale adoption.

AI Platform and Capability Development

• Define requirements for enterprise AI platforms, data infrastructure, and tooling.
• Partner with ICT teams to establish AI architecture and MLOps capabilities.
• Evaluate build-versus-buy decisions for AI solutions.
• Develop strategic partnerships with technology vendors, academia, startups, and innovation ecosystems.

Workforce Enablement and Change Management

• Lead AI adoption and change management efforts across the organization.
• Develop enterprise AI literacy and capability-building programs.
• Establish AI Communities of Practice and citizen development programs.
• Promote responsible and productive use of AI by employees.
• Drive cultural transformation toward data-driven and AI-enabled ways of working.

Executive Stakeholder Management

• Serve as the primary advisor to Executive Management on AI strategy and opportunities.
• Present AI portfolio performance, risks, and investment recommendations to executive committees.
• Facilitate alignment among business leaders, ICT, HR, Legal, Risk, Compliance, and Operations.
• Build executive sponsorship for strategic AI initiatives.

Qualifications

• Bachelor's degree in Engineering, Computer Science, Information Technology, Data Science, Business, Organizational Development, or related field.
• Master's degree preferred.
• MBA, Digital Transformation, AI, Data Analytics, or Strategy-related postgraduate qualifications highly desirable.
• 12-15+ years of progressive leadership experience.
• 5+ years leading enterprise transformation, digital transformation, data, analytics, automation, AI, or innovation initiatives.
• Demonstrated experience managing large cross-functional transformation programs.
• Proven track record in business value realization from technology-enabled transformation.