Senior Manager, AI Strategy and Platforms

About the Role

The Senior Manager, AI Strategy and Platforms leads the development and execution of the AI strategy, platform, and adoption agenda. This role translates business priorities into a coherent AI roadmap and practical operating processes, ensuring approved AI platforms are trusted, usable, and well-governed, while enabling colleagues to adopt AI responsibly at scale.

Key Responsibilities

Strategy, Roadmap, and Demand Portfolio

• Develop and maintain the enterprise AI strategy and roadmap, aligned to business priorities, Digital Products strategy, and platform capabilities.
• Provide recommendations on priorities and trade-offs to senior leadership.
• Manage a prioritized AI demand portfolio with clear problem statements, expected value, readiness criteria, and recommended routes to delivery.
• Manage the AI Factory's functional processes, including demand intake and qualification, prioritization criteria, business-readiness requirements, functional acceptance, adoption measures, and value-realization process.
• Create an approved, prioritized functional brief for each Factory engagement, covering the business problem, target users, expected value, process owner, governance route, business constraints, success measures, and adoption plan.
• Prepare investment logic and business cases for AI platforms, capabilities, and priority use cases.
• Support funding, budget planning, cost stewardship, and vendor decisions in partnership with Finance and Procurement.
• Track strategic outcomes, adoption, and value realization, using evidence to adapt priorities and roadmap decisions.

AI Platforms and Service Experience

• Develop platform-roadmap recommendations for enterprise AI platforms, model providers, and supporting services, balancing business value, user experience, scalability, risk, and cost.
• Manage the platform-service model, including target users, service catalog, onboarding paths, roles and permissions, support model, lifecycle standards, and platform runbooks.
• Monitor the AI platform as a business service, including user experience, adoption signals, access and support experience, provider performance, commercial fit, and vendor roadmaps.
• Lead business-side escalations and prioritization.
• Translate approved platform priorities into clear, actionable business requirements for Architecture and vendor partners.
• Maintain a clear, scalable approach to platform onboarding, access, usage standards, and lifecycle management.

Governance and Demand Management

• Implement and operate the AI governance model, including policies, decision rights, intake criteria, approval pathways, and governance forums.
• Ensure AI demand is assessed consistently for strategic fit, business value, data readiness, security, privacy, model risk, and adoption readiness.
• Coordinate governance decisions and escalations with Security, Legal, Privacy, Architecture, and business stakeholders, ensuring decisions, risks, and accountabilities are visible and actioned.
• Define and maintain standards for responsible AI use, roles and permissions, human oversight, model and agent usage, and acceptable business practices.
• Ensure governance is enabling rather than bureaucratic, maintaining appropriate control for the risk and scale of each use case.

Adoption, Literacy, and Capability

• Own the enterprise AI adoption strategy, including personas, target behaviors, adoption measures, literacy pathways, champion communities, and change interventions.
• Lead the AI literacy, enablement, and community agenda so employees can use approved AI tools confidently, safely, and productively.
• Sponsor practical adoption programs, onboarding waves, white-glove support, and feedback loops that convert platform access into sustained use and measurable business value.
• Partner with business leaders to identify barriers to adoption, strengthen local ownership, and embed AI into priority workflows.
• Establish repeatable adoption and value-realization practices—baselines, target measures, review cadence, and improvement actions—so AI becomes reliably and sustainably embedded in business workflows.

Leadership and Collaboration

• Manage and develop a small team of AI strategy, governance, platform, and adoption resources, setting clear objectives and collaboration practices.
• Act as a key business and platform interface for AI with executive stakeholders, business functions, enterprise architecture, security, finance, procurement, and vendors.
• Establish operating rhythms that connect strategy, demand, governance, platform requirements, and adoption readiness to delivery priorities.
• Represent the organization in relevant vendor and industry conversations; assess emerging capabilities for strategic relevance and controlled adoption.

Qualifications

• Significant experience leading enterprise AI, digital platforms, cloud platforms, or technology-enabled transformation in a global, complex organization.
• Demonstrated ability to develop strategy, operating processes, and multi-year roadmaps that connect business priorities, technology choices, and measurable value.
• Strong experience in platform adoption, product or service management, governance, change, enablement, or portfolio prioritization.
• Sound judgment in responsible AI, privacy, security, model risk, and governance, with the ability to make pragmatic, proportionate decisions.
• Experience managing senior stakeholders, cross-functional teams, and external technology partners.
• Ability to communicate a compelling AI vision and translate it into practical decisions, programs, and adoption actions for executive, business, and technical audiences.
• Strong analytical and commercial skills, including business cases, vendor evaluation, benefit tracking, and investment prioritization.
• Fluent English, written and spoken.