Director, AI Product Management
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IT/Tech
AI Business & Operations, IT Business Analyst, AI Evaluation
Job Description & How to Apply Below
Worldpac is seeking an experienced, director level AI Product Manager to accelerate the adoption of artificial intelligence across our high-volume wholesale distribution business focused on the automotive aftermarket. This role combines two responsibilities: (1) hands-on product leadership for Worldpac's AI solutions, owning the vision, roadmap, requirements, adoption, and business value of AI products and use cases; and (2) high-level oversight of the enterprise wide AI program rollout, ensuring the AI portfolio is prioritized, governed, coordinated, and reported on effectively.
This role provides AI program and portfolio-level oversight, sets priorities and success criteria, monitors progress and value realization, and partners closely with the PMO Project Managers to ensure AI initiatives are executed and deliver on Worldpac's strategy. The Director serves as Worldpac's primary owner of AI product strategy and operates as the connective leader between business stakeholders, AI engineering, data, security, the PMO, and external partners.
Key Responsibilities AI Product Strategy & Vision- Collaborate to define and own the AI product vision, strategy, and multi-year roadmap aligned with Worldpac's business objectives and AI maturity roadmap.
- Partner with executive and business leaders across Operations, Supply Chain, Sales, Finance, IT and HR to identify, evaluate, and prioritize high-value AI opportunities, including generative and agentic AI use cases.
- Work with departments to develop business cases for AI initiatives, including expected benefits, costs, risks, ongoing cost and resource requirements, and prioritize the portfolio based on impact, value, feasibility, and strategic fit.
- Monitor the AI market, vendor, and technology trends, and assess their relevance and applicability to wholesale distribution and the automotive aftermarket.
- Serve as product owner for Worldpac's AI products and use cases, translating business problems into clear product requirements, user stories, acceptance criteria, and success metrics.
- Own and prioritize the AI product backlog in partnership with AI engineering, data, architecture, and application teams.
- Lead discovery with business users, including process analysis, user interviews, and workflow mapping, to ensure AI solutions are designed around real operational needs.
- Guide solution design decisions related to AI models, AI platforms, data requirements, integrations, human-in-the-loop controls, and user experience, in partnership with AI engineers and enterprise architecture who collaborate on solution design and then provide architecture, technical design and tooling decisions.
- Oversee testing and validation of AI outputs for accuracy, reliability, and business fit prior to production release in collaboration with AI Engineering and Quality staff who validate accuracy and reliability. Accepts AI solutions for business fitness before release.
- Manage the full AI product lifecycle from ideation and pilot through production, scaling, continuous improvement, and retirement.
- Drive business adoption of AI solutions in partnership with business leaders, training, and change management resources.
- Define and track KPIs for each AI product, including adoption, productivity, cost savings, revenue impact, quality, and user satisfaction.
- Measure and report realized business value against business cases, and use results to refine roadmaps and investment decisions.
- Gather ongoing feedback from users and stakeholders to continuously improve AI products.
- Provide high-level oversight of the enterprise AI program rollout, ensuring alignment between the AI portfolio, roadmap, and business priorities.
- Own the AI intake and prioritization process, establishing clear criteria for evaluating, approving, and sequencing AI initiatives.
- Partner with the PMO, which is responsible for project planning, execution, and project management, to ensure AI projects are appropriately scoped, resourced, and aligned with product goals and success criteria.
- Monitor portfolio-level progress, dependencies, risks, and issues across AI initiatives, escalating and resolving cross-functional barriers as needed, without directly managing individual projects.
- Prepare and present AI portfolio status, value realization, and investment recommendations to the CIO, executive leadership, and, as required, the Board and parent‑company…
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