VP, Enterprise AI Enablement

EnerSys

VP of Enterprise AI Enablement at EnerSys overseeing AI strategy and integration with enterprise operations. Leading cross-functional teams to drive business value through AI initiatives.

Posted 5/4/2026full-timeRemote • 🇨🇭 SwitzerlandLeadWebsite

Tech Stack

Tools & technologies

Cyber SecurityERP

About the role

Key responsibilities & impact

Serve as EnerSys’ 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 aligned with growth, productivity, quality, safety, and risk objectives.
Advise the CIO, ELT, and Board on AI trends, risks, opportunities, and competitive implications.
Represent EnerSys externally with strategic AI partners, technology providers, and industry forums.
Design, implement, and continuously evolve the enterprise AI operating model, including governance forums, funding and intake processes, prioritization methods, and decision rights.
Chair and run the Executive AI Steering Committee, ensuring disciplined decision making, clear accountability, and execution follow through; set agendas, align key stakeholders, and communicate decisions and actions clearly.
Establish enterprise standards for responsible AI, data usage, security, privacy, and risk management in partnership with Legal, Cybersecurity, IT Architecture, HR, and Compliance.
Own AI investment governance, ensuring alignment with capital planning, transformation funding, and enterprise portfolio priorities.
Own the global AI use case portfolio and prioritization framework, balancing short term value delivery with long term strategic capability building.
Ensure AI initiatives progress efficiently from ideation to pilot to scaled production—eliminating “pilot only” stagnation.
Define, track, and report enterprise AI value metrics, including operational efficiency, cost reduction, quality improvement, risk mitigation, revenue enablement, and customer impact.
Regularly recalibrate the AI roadmap based on realized outcomes, business performance, and evolving priorities.
Orchestrate cross-functional delivery across IT, data, digital platforms, business units, and external partners—creating shared plans, clear ownership, and fast decisions.
Resolve enterprise level dependencies and escalations impacting delivery, adoption, or value realization by facilitating trade-off discussions, aligning decision makers, and driving timely, documented outcomes.
Ensure AI initiatives are integrated with core enterprise platforms (ERP, data environment, digital products) rather than delivered as isolated solutions.
Build scalable execution playbooks, delivery standards, and reusable components to accelerate adoption across regions and functions.
Partner with HR and Communications to lead enterprise-wide change management, AI literacy, and workforce enablement.
Sponsor AI capability building, including training programs, citizen developer models, communities of practice, and leadership education.
Drive cultural adoption by positioning AI as a core business capability embedded in how work gets done—not as a technology experiment.
Support workforce transformation planning, including role evolution, ethical considerations, and future skills development.
Build, lead, and develop a high performing enterprise AI organization with clear roles, succession, and career paths.
Set performance expectations, accountability, and development plans for direct and indirect reports.
Foster a strong culture of accountability, collaboration, and execution discipline across the AI ecosystem.

Requirements

What you’ll need

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, aligning multiple functions and regions to deliver shared outcomes.
Demonstrated success partnering with executive leaders and Boards on investment, governance, and transformation outcomes.
Demonstrated ability to influence senior stakeholders, facilitate tough trade-offs, 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.

Benefits

Comp & perks

Health insurance
401(k) matching
Flexible work arrangements
Professional development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI strategyenterprise AI operating modeldata usagerisk managementAI value metricschange managementtraining programscitizen developer modelsperformance expectationsaccountability

Soft Skills

leadershipcommunicationinfluencecollaborationexecution disciplinestakeholder managementdecision makingfacilitationcultural adoptionorganizational development