Senior Vice President, AI Strategy Lead

BNY Mellon•New York, NY

1d•$104,000 - $200,000•Onsite

About The Position

We’re seeking a future team member for the role of Senior Vice President, AI Strategy Lead. This role is located in New York City. In this role, you’ll make an impact by leading complex AI strategy workstreams and translating enterprise priorities into strategic themes, investment choices, operating-model recommendations, roadmaps, and executable plans. You will shape the AI Hub’s strategic agenda across AI-native platforms, digital employees, workflow automation, knowledge management, process reimagination, governed AI capabilities, and continuous intelligence. You will identify, assess, and prioritize AI opportunities based on business value, client impact, operational efficiency, strategic alignment, technical feasibility, control readiness, adoption potential, and implementation complexity. You will develop business cases, value hypotheses, cost-benefit analyses, KPI frameworks, adoption measures, and benefit-realization plans for priority initiatives. You will define how AI capabilities can help platforms become more intelligent, context-aware, governed, reusable, and scalable across enterprise workflows. You will advance continuous-intelligence priorities by connecting trusted data, governed AI, human judgment, operational context, and enterprise controls to practical business outcomes. You will develop recommendations for AI operating models, prioritization mechanisms, portfolio governance, investment sequencing, adoption strategies, and cross-functional accountability. You will produce executive-ready strategy narratives, decision papers, presentations, portfolio updates, and recommendations that simplify complex AI topics without overstating maturity or expected benefits. You will partner with Product, Engineering, Data, Operations, Finance, Risk, Governance, Legal, Compliance, Audit, and business teams to align strategy with execution feasibility and enterprise standards. You will ensure strategic recommendations address data readiness, responsible AI, model and technology risk, cybersecurity, privacy, resiliency, human oversight, regulatory considerations, and change management. You will track emerging developments across GenAI, agentic workflows, enterprise AI platforms, automation, data products, model providers, and market practices to inform strategic choices. You will establish portfolio transparency by defining consistent measures for initiative status, strategic alignment, adoption, value, dependencies, control readiness, and delivery progress. You will lead senior-stakeholder discussions, frame decision options, clarify tradeoffs, and drive alignment on priorities and recommended actions. You will build durable internal AI strategy capability by creating reusable strategic frameworks, analysis methods, decision templates, and value-measurement approaches. You will operate independently as a senior individual contributor, bringing structured judgment and executive-quality output to high-priority and often ambiguous enterprise initiatives.

Requirements

Typically 10+ years of experience in corporate strategy, strategy consulting, product strategy, AI/data strategy, enterprise transformation, or digital transformation.
Experience leading AI, GenAI, automation, data, analytics, or technology-enabled transformation initiatives.
Strong commercial judgment and experience developing business cases, roadmaps, KPIs, and executive recommendations.
Demonstrated ability to influence senior stakeholders in a global, matrixed organization.
Bachelor’s degree required

Nice To Haves

Financial-services and responsible-AI experience are preferred.
MBA or relevant Master’s degree preferred.

Responsibilities

Lead complex AI strategy workstreams and translate enterprise priorities into strategic themes, investment choices, operating-model recommendations, roadmaps, and executable plans.
Shape AI Hub’s strategic agenda across AI-native platforms, digital employees, workflow automation, knowledge management, process reimagination, governed AI capabilities, and continuous intelligence.
Identify, assess, and prioritize AI opportunities based on business value, client impact, operational efficiency, strategic alignment, technical feasibility, control readiness, adoption potential, and implementation complexity.
Develop business cases, value hypotheses, cost-benefit analyses, KPI frameworks, adoption measures, and benefit-realization plans for priority initiatives.
Define how AI capabilities can help platforms become more intelligent, context-aware, governed, reusable, and scalable across enterprise workflows.
Advance continuous-intelligence priorities by connecting trusted data, governed AI, human judgment, operational context, and enterprise controls to practical business outcomes.
Develop recommendations for AI operating models, prioritization mechanisms, portfolio governance, investment sequencing, adoption strategies, and cross-functional accountability.
Produce executive-ready strategy narratives, decision papers, presentations, portfolio updates, and recommendations that simplify complex AI topics without overstating maturity or expected benefits.
Partner with Product, Engineering, Data, Operations, Finance, Risk, Governance, Legal, Compliance, Audit, and business teams to align strategy with execution feasibility and enterprise standards.
Ensure strategic recommendations address data readiness, responsible AI, model and technology risk, cybersecurity, privacy, resiliency, human oversight, regulatory considerations, and change management.
Track emerging developments across GenAI, agentic workflows, enterprise AI platforms, automation, data products, model providers, and market practices to inform strategic choices.
Establish portfolio transparency by defining consistent measures for initiative status, strategic alignment, adoption, value, dependencies, control readiness, and delivery progress.
Lead senior-stakeholder discussions, frame decision options, clarify tradeoffs, and drive alignment on priorities and recommended actions.
Build durable internal AI strategy capability by creating reusable strategic frameworks, analysis methods, decision templates, and value-measurement approaches.
Operate independently as a senior individual contributor, bringing structured judgment and executive-quality output to high-priority and often ambiguous enterprise initiatives.