VP, Enterprise AI Enablement

Responsibilities

• Serve as Ener Sys’ executive leader and single point of accountability for enterprise AI strategy, execution, and outcomes.
• Translate enterprise and business strategies into a clear, multi‑year AI vision and roadmap.
• Advise the CIO, ELT, and Board on AI trends, risks, opportunities, and competitive implications.
• Represent Ener Sys externally with strategic AI partners, technology providers, and industry forums.
• Design and implement the enterprise AI operating model, including governance forums and funding processes.
• Establish enterprise standards for responsible AI, data usage, security, privacy, and risk management.
• Own AI investment governance, ensuring alignment with capital planning and transformation funding.
• Own the global AI use case portfolio and prioritization framework.
• Define, track, and report enterprise AI value metrics.
• Orchestrate cross-functional delivery across IT, data, and business units.
• Partner with HR to lead enterprise-wide change management and AI literacy initiatives.
• Build, lead, and develop a high performing enterprise AI organization with clear roles.

• 10+ years of experience leading enterprise scale transformation, digital programs, or technology enabled business initiatives.
• Proven executive experience building and operating enterprise-level capabilities in a global environment.
• Demonstrated success partnering with executive leaders and Boards on investment, governance, and transformation outcomes.
• Demonstrated ability to influence senior stakeholders and communicate clearly across technical and non-technical audiences.
• Strong background working with consulting and technology partners and transitioning ownership into sustainable internal operating models.
• Deep exposure to AI, advanced analytics, automation, or data driven platforms in complex, regulated, or industrial environments.
• Manufacturing, industrial, or global operating model experience is strongly preferred.

• AI strategy
• enterprise AI operating model
• data usage
• risk management
• AI value metrics
• digital transformation
• advanced analytics
• automation
• data driven platforms
• governance

• leadership
• communication
• influence
• change management
• collaboration
• strategic thinking
• stakeholder engagement
• organizational development
• cross-functional delivery
• problem solving