Role Overview
The VP of AI will lead enterprise-wide AI strategy and transformation, acting as the executive owner for AI adoption, governance, capability building, and value realization. This role is responsible for aligning AI investments with company strategy, enabling business-wide adoption, and ensuring responsible, scalable implementation of AI across the organization.chiefjobs+1
Requirements
Key Responsibilities
- Define, communicate, and execute the company-wide AI vision, strategy, roadmap, and success metrics.
- Prioritize the AI portfolio, balancing short-term wins with long-term platform and capability investments.
- Partner with C-suite leaders and business heads to identify opportunities where AI can improve growth, efficiency, and customer outcomes.
- Lead cross-functional teams spanning AI/ML, transformation, product, change management, and technical program delivery.
- Establish AI governance structures, policies, and review mechanisms for ethics, compliance, explainability, and third-party risk.
- Sponsor AI centers of excellence, sandbox programs, innovation labs, and enterprise AI literacy initiatives.
- Oversee integration of AI solutions into enterprise systems, business processes, and operating models.
- Drive organization-wide change management and workforce readiness for AI adoption.
- Serve as the executive ambassador for AI internally and externally, including board updates, partner discussions, and industry representation.
Required Qualifications
- 12+ years of experience in AI/ML, enterprise technology, digital transformation, or data-driven product leadership, including 5+ years in executive leadership roles.
- Proven success scaling AI initiatives across large or matrixed organizations.
- Strong understanding of AI/ML technologies, cloud ecosystems, enterprise architecture, and business transformation.
- Experience building governance frameworks for responsible AI and data usage.
- Excellent executive presence, communication, and stakeholder influence.
Preferred Qualifications
- Advanced degree in Computer Science, Data Science, Engineering, Business Administration, or related discipline.
- Experience briefing boards, regulators, or external partners on AI strategy and risk.
- Experience leading enterprise change management, capability building, and AI operating model design.
Suggested skills
For either title, the strongest candidate profile usually combines these skill areas:
- AI/ML strategy and roadmap ownership.digitalwaffle+1
- Production-grade model deployment and lifecycle management.
- Cross-functional leadership across product, engineering, legal, and operations.digitalwaffle+1
- Responsible AI, compliance, and governance.digitalwaffle+1
- Business case creation, KPI tracking, and executive reporting.
