AI Adoption & Commercialization Senior Lead - Senior Vice President
Citigroup
- Location
- New York New York United States
- Work model
- On-Site
- Level
- Staff
- Posted
- Aug 24, 2026
About this role
Citi Services provides global solutions that help corporations, financial institutions, public sector and commercial clients optimize operations and drive their business forward. Through our five business lines – Liquidity Management Services, Payments, Trade & Working Capital Solutions, Investor Services and Issuer Services - we provide cash management, payments/receivables solutions, working capital solutions, post-trade securities services and issuer services across Citi’s global network. We are looking for an AI Adoption & Commercialization Senior Lead to own the vision, strategy, and measurable outcomes of AI solutions across clusters and countries — driving both client-facing value and internal agility at scale. Sitting within the Platforms and Data Services organization, this role places you to drive adoption and impact from AI use cases we develop- that serves clients, our Service agents, Operations and across our Liquidity, Payments, Trade & Working Capital, Investor Services, and Issuer Services businesses.
Key Responsibilities
Adoption & Commercialization Drive adoption of enterprise tools and AI solutions across Citi Services. Provide structured feedback on AI solution usability and outcomes. Educate CCO, Banking, and Sales stakeholders on use case value. Represent Services' needs and progress to local regulators and senior leadership, securing alignment and investment. Training and driving the use of Enterprise AI tools Drive or conduct trainings of Enterprise AI tools, track adoption numbers, track usage and drive focused training where adoption is low. Economic Value & KPI Management, Own data and analytics dashboards on adoption and communicate frequently Define, track and report on KPIs per use case per cluster and country. Also define and drive adoption and commercialization standard KPIs. Measure financial return based on investment vs. value generation — including running cost, cost-to-serve versus realized return. Build dashboards and reporting cadences that translate AI investment into board-level financial narratives and justify continued funding. Local Use Case Generation & Global Execution: Collaborate, form swat team of AI accelerators from product / ops / tech / IBR, go deeper and develop relevant AI use case. Ensure client needs are represented, and adherence to local regulations and control frameworks, and share market disruptors. Work closely with Product, global and Services AI Central team, present and participate in execution. Participate in use cases and do design thinking and ensure cluster client perspectives are included in the execution. Client & Market Intelligence Conduct client and competitor market research to identify gaps, inform the product innovation roadmap, and differentiate Citi's AI offering. Co-create AI products with clients. Continuously learn the latest use cases, risks, and strategies for implementing AI at a global scale. Knowledge Sharing & Best Practices Disseminate AI best practices, lessons learned, and use case blueprints. Create internal communities of practice and connect regional clusters to accelerate AI adoption and avoid duplicative effort across the organization. Educate local teams, leaders and country heads and prepare them for regulatory reporting Regulatory reporting Understand and decode local regulations and provide to global team to build observability to meet regulatory requirements. Provide regulatory reports as needed by countries or cluster MBR and Leadership Metrics Own and report AI Adoption and usage metrics in Cluster head and country head MBRs, make them aware, educate them and help them track AI index in clusters, countries, their clients and local employees. Additional Responsibilities Cross-Functional & Innovation Mandate Create industry-leading AI experiences for clients and leverage the latest technologies to drive innovative features in how users interact with data and complete tasks Partner closely with Engineering,