Director, AI Enablement

Overview

At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges. Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose.

Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve. You’ll have opportunities to learn and lead in a forward‑thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about—locally and globally. Come make an impact every day at Zebra.

The Director, AI Enablement is responsible for enabling consistent, scalable, and responsible internal AI adoption across Product & Solutions (P&S). This role establishes the operating model, alignment mechanisms, and practical guardrails that allow P&S organizations to independently drive AI enabled improvements while ensuring those efforts align with enterprise requirements and P&S priorities.

• Establish and maintain a clear, repeatable operating model for internal AI adoption across P&S, ensuring AI initiatives consistently address workflow design, risk considerations, reuse opportunities, adoption planning, and outcome measurement.
• Provide portfolio level visibility into AI initiatives across P&S, actively engaging with execution teams to identify duplication, conflicting approaches, and opportunities to scale effective solutions.
• Maintain a reuse register capturing AI patterns, workflows, agents, vendors, and lessons learned, and actively guide teams toward reuse where it improves scale, cost, or consistency.
• Translate enterprise AI governance, security, legal, and regulatory requirements into practical, actionable expectations for P&S teams, working directly with execution leaders to integrate requirements into existing workflows.
• Serve as an active thought partner to PMO, Engineering, and Product leaders, helping teams reason through how AI should be applied, where it adds value, and how success should be measured in the context of their workflows.
• Establish a common measurement framework for AI adoption across P&S and work with execution teams and analytics partners to enable consistent visibility into adoption, productivity, and business outcomes using team‑defined metrics.
• Lead and develop an internal business intelligence team, guiding their evolution toward predictive analytics and foundational data readiness to support the broader AI operating model.
• Capture successful AI practices emerging from execution teams and enable reuse through shared guidance, reference examples, and cross‑team knowledge sharing.
• Drive alignment and outcomes across P&S through influence, partnership, and guidance, enabling teams to independently execute AI‑enabled improvements within shared standards.
• Act as a trusted advisor to P&S leadership by synthesizing AI adoption trends, outcomes, and maturity to support executive decision‑making and cross‑functional alignment.
• Identify and escalates alignment issues at both the team and organizational level that create material risk, cost, or scalability concerns for AI adoption across P&S.

• Bachelor’s degree in Engineering, Computer Science, Data Science, or a highly quantitative related field.
• Minimum 10+ years of progressive leadership experience in product development, digital transformation, data science/analytics or related domains with significant exposure to AI enabled initiatives.
• Minimum of 5+ years’ operating as part of a product development team.
• Experience delivering transformation initiatives spanning multiple business units or global geographies, supported by verifiable metrics such as number users impacted and percent efficiency gains.
• Direct people management experience leading and developing data analytics, business intelligence (BI), engineering, data science, or technical program/product management…