AI Strategy Lead

Responsibilities

• Lead an Agentic AI domain, owning how that domain maps to and enables the Group’s business priorities and outcomes.
• Work with domain and business leaders to identify, frame, and prioritise Agentic AI opportunities and use cases, ensuring choices are grounded in commercial and operational reality.
• Assess priorities across the full Agentic AI lifecycle, from inception and capability definition through build, deployment, adoption, and value realisation, identifying gaps and strengthening weak points.
• Build and maintain a realistic, scalable domain roadmap, orchestrating work across business units, platforms, and enabling teams.
• Translate business objectives into agentic and technical requirements, with sufficient understanding of data, integration, and system dependencies to make the strategy credible and executable.
• Engage and influence senior stakeholders to secure alignment, resolve competing priorities, and agree clear OKRs—maintaining a single, coherent domain narrative across value, governance, platforms, skills, and change.
• Define domain-level value outcomes and track realisation, ensuring Agentic AI initiatives remain outcome-led rather than activity-driven.
• Drive operating-model change and business adoption, shaping how agents, teams, controls, and processes come together to make Agentic AI effective in practice.
• Promote cross-functional collaboration and reuse across business domains and Agentic AI ecosystem, reducing duplication and accelerating scale.
• Lead and develop a small team of strategy managers within the AI CoE, creating focus, delivery discipline, and synergy across Agentic AI domains.

Requirements

• A strong understanding of AI and Agentic AI, including how these capabilities scale in practice across platforms, operating models, controls, and enterprise-wide adoption.
• Familiarity with the core building blocks of Agentic AI—data, integration, infrastructure, and orchestration—and how they come together to enable robust, scalable solutions.
• Experience translating business priorities into clear AI and Agentic AI strategies, value cases, and actionable roadmaps.
• The technical depth to engage confidently with platform and engineering teams, alongside the ability to operate effectively with senior business leaders.
• Strong strategic judgement and commercial awareness, grounded in real-world experience of what works (and what doesn’t).
• Experience leading or shaping large-scale AI or Agentic AI initiatives, from early strategy through to delivery and value realisation.

ATS Optimization Keywords

• Hard Skills: Agentic AI, AI, data, integration, infrastructure, orchestration, strategy development, roadmap creation, value realisation, operating model change, cross-functional collaboration.
• Soft Skills: strategic judgement, commercial awareness, stakeholder engagement, influence, team leadership, delivery discipline, focus, synergy, communication, problem-solving.