SVP, Enterprise AI Strategy

Reinsurance Group of America, Incorporated•Chesterfield, MO

2d•Hybrid

About The Position

You desire impactful work. You’re RGA ready RGA is a purpose-driven organization working to solve today’s challenges through innovation and collaboration. A Fortune 200 Company and listed among its World’s Most Admired Companies, we’re the only global reinsurance company to focus primarily on life- and health-related solutions. Join our multinational team of intelligent, motivated, and collaborative people, and help us make financial protection accessible to all. The SVP, Artificial Intelligence Strategy is a newly established executive leadership role responsible for defining and driving the enterprise-wide AI vision for a Global Fortune 200 reinsurer. Reporting directly to the EVP, Chief Strategy Officer, this officer-level position will serve as the enterprise leader for AI strategy — translating complex technological capabilities into durable competitive advantage across employee productivity, business process efficiency (underwriting, claims, etc.), and transformational business opportunities to drive differentiation in the market. Operating at the intersection of reinsurance domain expertise, advanced analytics, and corporate strategy, the SVP partners closely with the Chief Information Officer, Chief Strategy Officer, and other C‑suite leaders, as well as global business units and the Board to ensure AI becomes a core driver of profitable growth, operational resilience, and market differentiation.

Requirements

Education: Advanced degree (Master's or Ph.D.) in Computer Science, Data Science, Statistics, Actuarial Science, or a related quantitative field; MBA a plus
Work Experience: 15+ years of progressive experience in AI/ML, advanced analytics, or technology strategy
5+ years in a senior executive leadership role (VP or above) with P&L or enterprise-wide program accountability
Demonstrated experience in the (re)insurance, financial services, or risk management sector
Skills & Abilities: Deep expertise in ML/DL frameworks, generative AI, NLP, and large-scale data platform architecture
Proven track record deploying production AI systems in regulated, mission-critical environments
Exceptional executive presence with ability to influence Board-level stakeholders
Strong grasp of global AI regulatory landscape and responsible AI principles
Experience operating across multiple geographies and matrixed global organizations

Responsibilities

Enterprise AI Strategy & Governance: Architect and steward the multi‑year enterprise AI strategy, establishing a prioritized enterprise roadmap that aligns AI investments with corporate strategy, risk appetite, and global growth objectives. Define enterprise guardrails, standards, and prioritization frameworks to guide business‑led AI initiatives, ensuring alignment, coherence, and value realization across regions and functions. Partner with business and regional leaders to translate enterprise ambitions into executable programs with clear milestones, resource implications, and measurable ROI.
C-Suite & Board Engagement: Serve as the primary executive advisor to the C-suite and Board on AI trends, risks, and opportunities within the reinsurance and broader financial services landscape. Prepare and present governance-ready materials, including AI risk disclosures, ethical frameworks, and strategic updates for Audit, Risk, and Technology committees.
AI‑Enabled Business Transformation & Value Creation: Partner globally across the business and enablement functions to embed AI and machine learning across three core value areas: Employee productivity – scaling AI-enabled tools and ways of working that improve efficiency, decision quality, and capacity across teams. Business process efficiency – embedding AI into core processes (e.g., underwriting, claims, operations) to drive speed, quality, and cost efficiency. Transformational business opportunities – identifying and advancing AI-enabled capabilities that create differentiation, new value propositions, and competitive advantage in the market.
AI Governance, Ethics & Regulatory Compliance: Establish and chair the enterprise AI Governance Council, developing policies for responsible AI use including model explainability, algorithmic fairness, data privacy, and regulatory compliance across all operating jurisdictions. (. Ensure AI practices withstand regulatory scrutiny and reputational risk.
AI Leadership & Operating Model: Define CoE operating model — including shared services vs. embedded team structures — to accelerate AI deployment velocity across global business units while maintaining rigorous model validation standards.
Strategic Partnerships & Ecosystem Development: Identify, negotiate, and manage strategic partnerships with leading AI technology providers, academic institutions, and industry consortia. Evaluate build/buy/partner decisions for AI capabilities, and oversee vendor selection, contract governance, and performance accountability for AI-related technology relationships. Continually survey the market for insure tech investment and acquisition opportunities.
AI Infrastructure & Data Strategy: In partnership with the Head of Data [title still TBD] and CIO, define the enterprise data strategy required to sustain AI at scale — encompassing data architecture, lineage, quality, and accessibility. Drive investment decision regarding platform and infrastructure to ensure a robust technical foundation for advanced AI capabilities.
Client-Facing AI Innovation & Cedent Value Creation: Develop a strategy for AI-powered tools, insights, and service offerings that create measurable value for cedents, brokers, and distribution partners. Coordinate with the business on the commercialization of proprietary AI assets — including risk scoring models, claims prediction tools, and portfolio analytics platforms — as differentiating client engagement capabilities.
AI Literacy, Culture & Change Management: Cultivate an enterprise-wide AI-fluent culture by designing and sponsoring targeted learning programs for all associates. Ensure organizational change management exist for AI-driven workflow transformation, ensuring workforce readiness, adoption, and trust in AI-assisted decision-making.
AI Performance Measurement & Value Realization: Define, track, and report a comprehensive set of AI KPIs — spanning operational efficiency gains, speed-to-insight, and model performance metrics — to demonstrate value realization and guide ongoing AI investment prioritization. Present quarterly AI performance scorecards to executive leadership and, as needed, the Board.

Benefits

RGA also maintains a full range of health, retirement, and other employee benefits.
RGA is an equal opportunity employer. Qualified applicants will be considered without regard to race, color, age, gender identity or expression, sex, disability, veteran status, religion, national origin, or any other characteristic protected by applicable equal employment opportunity laws.

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