Lead BMBS AI transformation agenda — Define and continuously evolve a pragmatic AI transformation roadmap for BMBS, translating leadership ambition into clear priorities, workstreams, ownership and milestones, with a strong focus on operational efficiency, customer lifecycle improvement, dealer effectiveness and scalable capability building.
Drive cross-functional execution and organizational alignment — Act as the central transformation lead across business functions, IT, D&C and HR to align stakeholders around a shared AI agenda, strengthen business ownership, reduce fragmented experimentation, and build an effective central-plus-BU operating model with clear accountabilities.
Identify, prioritize and scale high-value AI use cases — Steer the AI portfolio from ideas and pilots toward the most relevant, business-backed use cases, ensuring efforts are prioritized based on value, feasibility, scalability and strategic relevance, especially in areas that improve productivity, decision quality, customer experience and frontline/dealer impact.
Build the foundation for sustainable AI adoption — Strengthen the enabling layer required for scale, including data accessibility and quality, knowledge foundations, governance, tools, capability building and adoption mechanisms, while ensuring AI initiatives are embedded into business processes rather than remaining isolated or purely technology-driven.
Ensure measurable impact through KPI and value steering — Establish clear objectives, KPI logic, monitoring routines and management reporting mechanisms to make AI value visible, support resource decisions, and ensure the transformation delivers tangible business outcomes rather than activity without impact.
