Vice President - AI Operations Transformation

If you want to achieve more in your mission of health care, you have to be really smart about the business of health care. Challenge yourself, your peers and our industry by shaping what health care looks like and doing your life's best work.(sm) Lead the end-to-end AI-led operations transformation strategy, with accountability for defining the multi-year roadmap and delivering measurable business outcomes (cost, productivity, quality, experience, and cash acceleration). Own the identification, prioritization, and scaling of AI-driven opportunities across operations, working in close partnership with Operations, Technology and Product organizations to ensure fit-for-purpose enablement-without assuming build ownership. Drive the operating model, governance, and behavioral changes required to embed AI into core workflows at enterprise scale.

Boundary / Guardrail This role is a business and operations leadership position. While it defines AI transformation strategy and co-creates solutions with Technology and Product teams, it does not own engineering delivery or platform development. 1. AI-Led Operations Transformation Strategy & Value Agenda · Define a multi-year AI Operations transformation roadmap, aligned to enterprise priorities and business value goals. · Identify and size transformation opportunities across core operational domains and enabling functions, eg RCM, PI, RQ, EEB, LS, Quality, WFM · Build and continuously refine a prioritized portfolio of AI initiatives, balancing impact, feasibility, and time-to-value. · Establish clear linkage between AI investments and business outcomes, with ownership of value realization. 2. Value Realization & Business Accountability · Own delivery of committed financial and operational outcomes including cost reduction, capacity creation, revenue uplift, quality improvement, and experience gains in partnership with ops COOs. · Embed AI initiatives into business performance management systems, KPI structures, and operating reviews. · Drive accountability within operations leadership for sustained value capture, not just deployment. 3. Cross-Functional Orchestration · Act as the single-threaded operations owner for AI transformation initiatives. · Partner with Technology and Product teams and support solutions development aligned to business priorities and operational realities. · Define business requirements, success metrics, and adoption expectations while enabling Tech and Product teams to deliver scalable solutions. · Drive enterprise-level prioritization and trade-off decisions across competing initiatives. 4. Operating Model Transformation & Workflow Redesign · Redesign end-to-end processes, workflows, and decision layers to embed AI into how work is performed. · Ensure AI is integrated into day-to-day operations rather than deployed as standalone tools. 5. Scaling & Industrialization · Drive enterprise-scale replication and adoption of proven AI use cases across business units and geographies. · Establish repeatable playbooks for scaling and adoption, including rollout strategy, training, and performance tracking. 6. Governance, Funding & Decision Rights · Establish and lead AI governance for Operations, including portfolio prioritization, funding allocation, and performance tracking. · Define clear decision rights across Operations, Technology, and Product. · Lead executive-level reviews on transformation progress, risks, and value delivery. 7. Adoption, Change & Capability Building · Drive enterprise adoption of AI within operations, ensuring sustained usage and impact. · Lead change management, capability building, and leadership alignment. · Define and track adoption KPIs (usage, productivity gains, quality improvements). · Ensure strong business ownership and accountability for outcomes. · Communicate transformation progress to executive leadership and stakeholders. 8. Ecosystem & Acceleration · Evaluate and leverage external partners, vendors,