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JD Power

Head of AI Enablement

Department
Engineering
Job Type / Location
remote
Experience Required
10+ years
Posted On

About the Role

JD Power is seeking its first dedicated Head of AI Enablement. While JD Power has invested in AI, this role formalizes the function, sets standards, and accelerates enterprise-wide adoption. The successful candidate will personally drive technical decisions, prototypes, and tooling to scale AI usage across the company, ensuring every relevant business unit and workflow effectively utilizes AI. This is a builder role, focused on coordinating AI efforts, establishing common standards, and translating momentum into measurable enterprise impact. The position reports to the Chief Product & Technology Officer and has board-level visibility.

Responsibilities

  • Personally evaluate, prototype, and make decisions on AI tools and platforms for enterprise adoption, including hands-on testing of agents, models, and orchestration layers.
  • Build internal tools, dashboards, prototypes, and reference implementations to demonstrate effective AI adoption.
  • Define and execute the enterprise-wide AI adoption strategy, including metrics, milestones, and reporting for executive leadership and the board.
  • Formalize and operate the AI Enablement Hub as a cross-functional capability, defining its operating model, intake, prioritization, decision rights, and cadences.
  • Build and lead a distributed Champions network embedded within business units, coordinating their delivery efforts within their respective functions.
  • Chair the AI Steering Committee, acting as the senior point of coordination across various departments including CPTO, CDAO, CHRO, Legal, Risk, and business unit leaders.
  • Define and operationalize JD Power’s AI governance framework, including policies, guardrails, and responsible-AI guidelines, from a builder’s perspective.
  • Partner with HR on AI skills development, role evolution, and the workforce implications of AI productivity gains.
  • Develop business cases for AI investments and own value delivery across the portfolio.
  • Communicate AI strategy to internal and external audiences, including the board and PE owner, using clear business language.

The role requires strong prioritization and the ability to operate at pace, making decisions quickly and driving real AI impact while the structure is being formalized. The proportion, sequencing, and operating model are yours to shape, with the Hub designed to scale alongside the work.

Preferred Skills

  • IC Readiness: An individual contributor with executive sponsorship, energized by personally building and shipping. Not dependent on a team underneath.
  • Workforce Enablement and Cultural Change: Demonstrated experience driving adoption of new technology or ways of working across large organizations, even without initial demand from the business.
  • Governance, Responsible AI, and Enterprise Data: Working knowledge of responsible-AI practices, data classification, and the movement of regulated data through AI systems, including boundaries for hosted models, private inference, and legal review. Ability to write usable policies.
  • Enterprise Scale and Cross-Functional Influence: Ability to operate across business and technical functions without direct authority, with credibility among senior engineering leaders. Capable of delivering tough messages to executives and gaining buy-in from resistant business units.

A relevant degree is a a plus, but equivalent experience is weighted equally. Industry background is open, including financial services, professional services, B2B data, and tech, provided the candidate has experience in an environment with mature engineering and a thoughtful executive team.

Basic Qualifications

  • Ability to influence and collaborate across business and technical teams without direct authority.
  • Strong communication skills, comfortable presenting to executive leadership and facilitating working sessions.
  • Experience driving technology adoption and organizational change at scale.
  • Experience in data-intensive or research-driven environments.
  • Familiarity with governance, risk, compliance, or responsible AI frameworks.
  • Understanding of data privacy regulations and enterprise AI platforms such as Microsoft Copilot, Gemini Enterprise, Claude, or ChatGPT Enterprise (preferred).

View Assessment Process

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