Staff Vice President (VP) Enterprise AI Governance, Risk & Operational Excellence

Title: Staff Vice President (VP) Enterprise AI Governance, Risk & Operational Excellence Job Description: Staff Vice President (VP) Enterprise AI Governance, Risk & Operational Excellence Location:   May be located in any Elevance Health PulsePoint office preferably in Indianapolis, IN, Atlanta, GA, Mason, OH, Richmond, VA, Norfolk, VA or Woodland Hills, CA. This role requires associates to be in-office at least 3 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered.  Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law.

The Staff Vice President, Enterprise AI Governance, Risk & Operational Excellence is the enterprise executive responsible for transforming technology and AI governance into a disciplined, responsive, and scalable operating capability. This leader will establish the mechanisms that allow Elevance Health to innovate with speed while maintaining trust, transparency, regulatory compliance, and clear accountability. This executive will connect Legal, Compliance, Risk, Security, Data, Technology, and the Business to resolve complex issues quickly, translate requirements into practical controls, and embed governance directly into enterprise workflows. The role combines strategic judgment with hands-on operational leadership across Responsible AI, enterprise governance, regulatory readiness, process automation, workforce enablement, and value realization.

Scope 7 direct reports / 25+ total FTEs Position Responsibilities 1. Enterprise AI Governance and Responsible AI • Own and continuously advance the enterprise operating model for Responsible AI, including decision rights, risk-tiering, review pathways, escalation mechanisms, human oversight, and ongoing monitoring. • Translate Responsible AI principles into enforceable standards, repeatable controls, evidence requirements, and practical guidance for technology and business teams. • Establish governance across the AI lifecycle, from intake and use-case assessment through development, deployment, monitoring, change management, and retirement. • Ensure AI governance addresses traditional, generative, agentic, and emerging AI capabilities without creating unnecessary barriers to responsible innovation. 2. Regulatory Strategy, Compliance and Audit Readiness • Anticipate, assess, and operationalize evolving federal and state requirements affecting AI, data, privacy, technology, and healthcare operations. • Partner with Legal, Compliance, Privacy, Risk, Government Affairs, and Internal Audit to convert regulatory interpretation into clear enterprise requirements, controls, ownership, and evidence. • Maintain a traceable view of obligations, policy decisions, risk acceptances, exceptions, control performance, and remediation actions. • Prepare the organization for regulatory inquiries, audits, examinations, and executive or board-level oversight with reliable documentation and transparent reporting. 3. Cross-Enterprise Decision Leadership • Chair or lead decision forums that bring together Legal, Compliance, Risk, Security, Data, Technology, Operations, and Business leaders to resolve issues at the right level and pace. • Create clear decision rights, escalation paths, service-level commitments, and accountability so issues do not stall across organizational boundaries. • Frame complex tradeoffs in business terms, clarify residual risk, and drive documented decisions that leaders can execute. • Build trusted relationships while maintaining the independence and judgment