Divisional Artificial Intelligence (AI) Adoption Manager

About the role

We are seeking an experienced AI Adoption Manager (Divisional) to play a critical role in shaping how AI drives efficiency and transformation across the business.

Responsibilities

• Work with functional leaders to surface high-value ideas and convert them into structured use cases.
• Proactively identify opportunities to apply AI across business functions by analyzing workflows, inefficiencies, and manual effort.
• Build and maintain a prioritized pipeline of AI initiatives based on impact, feasibility, and ROI.
• Continuously generate new ideas by combining business insight with emerging AI capabilities.
• Act as the primary interface between business stakeholders and engineering teams.
• Translate business problems into clear AI requirements, use cases, and solution briefs.
• Partner closely with AI engineers and 3rd party vendors who design and deploy the solutions.
• Ensure alignment between intended business outcomes and technical delivery.
• Define success metrics upfront for every AI initiative (e.g. time saved, cost reduction, revenue uplift, accuracy improvements).
• Build robust frameworks to measure: Adoption and usage, Productivity gains, Financial impact / ROI.
• Track performance post-deployment and ensure benefits are realized and sustained.
• Establish consistent reporting to demonstrate value and inform prioritization.
• Continuously refine use cases based on performance data.
• Drive adoption of AI solutions through structured rollout, training, and engagement.
• Identify change impacts and ensure solutions are embedded into daily workflows.
• Develop playbooks, usage guidance, and best-practice frameworks.
• Support teams to integrate AI into how they work — not as a bolt-on.
• Maintain a pipeline of pilots and rapid experiments with new AI tools and approaches.
• Work with engineers and 3rd party vendors to test, validate, and scale solutions quickly.
• Stay up to date on emerging AI technologies and assess practical business applications.
• Ensure a balance between experimentation and measurable outcomes.
• Ensure solutions are documented, repeatable, and ready for deployment across regions.
• Develop onboarding packs and training materials for scaling.
• Maintain consistency while enabling regional adaptation.
• Ensure all AI initiatives are aligned to Group and Divisional AI governance, data policies, and IS standards from the outset.
• Identify when IS engagement and approvals are required and plan accordingly.
• Define data sensitivity, risk level, and compliance requirements at use-case stage.
• Own coordination of IS engagement from a business and delivery perspective.
• Own the end-to-end process for AI Steering Group submissions, including pilots and go-live approvals.
• Define and coordinate all required inputs for decision-making, including: Business case and ROI projections, Success metrics and measurement approach, Use-case definition and scope, Risk, governance, and compliance considerations.
• Present AI initiatives to the Steering Group, clearly articulating: Expected value and impact, Risks and mitigations, Readiness for pilot or scale.
• Own tracking of decisions, actions, and follow-ups from the Steering Group.
• Ensure all initiatives meet approval before pilot and go-live.

Qualifications

• Bachelor’s degree in Business, Information Technology, Computer Science, Engineering, or a related field.
• 5+ years of experience in AI adoption, digital transformation, process improvement, automation, or technology implementation.
• Proven ability to identify business opportunities and translate them into technology-driven solutions.
• Experience leading cross-functional projects from concept through deployment and adoption.
• Strong understanding of AI, Generative AI, automation, analytics, and emerging digital technologies.
• Demonstrated success building business cases, defining KPIs, and measuring ROI.
• Experience collaborating with business leaders, technical teams, and third-party vendors.
• Strong project management, stakeholder management, and change management skills.
• Excellent communication, presentation, and executive-facing skills.
• Knowledge of data governance, information security, compliance, and responsible AI practices.
• Willingness to travel up to 30–40% as required.