A Career at HARMAN As a technology leader that is rapidly on the move, HARMAN is filled with people who are focused on making life better. Innovation, inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together, you’ll discover that at HARMAN you can grow, make a difference and be proud of the work you do every day. About the Role We are seeking an AI Transformation Manager Operations to drive value-stream-based AI transformation across Automotive Operations.
This role translates the Operations AI strategy into executable initiatives that redesign end-to-end processes, strengthen data foundations, and embed AI into operational decision-making. The role combines strategic, functional, transformational and technical capabilities, with focus on priority value streams such as E2E Costing, Risk Management or Supply Chain Visibility & Resilienc. Your Team This role reports to the AI Strategy Lead Operations within the Operations Excellence Digitalization organization.
You will collaborate with Operations Excellence leadership, BI & Dataworks, IT, Digitalization, Data Architecture and key functional stakeholders across Procurement, Supply Chain, Manufacturing, Finance, Engineering and SBUs. What You Will Do 1. Lead AI Value Stream Transformation Lead selected AI transformation value streams from opportunity framing through process redesign, data scoping, solution concept, implementation support and adoption.
Drive holistic redesign across process, people, data, digitalization and AI, ensuring AI is embedded into the future-state operating model. Translate strategic focus areas such as E2E Costing, Risk Management, Supply Chain Visibility, Manufacturing GPT and Operations 360 into actionable transformation charters and roadmaps. Define measurable value targets, including cost impact, efficiency gains, lead-time reduction, resilience improvement, risk reduction and decision-speed improvement.
2. Redesign Operations Processes with AI Embedded Redesign end-to-end operational processes with AI embedded by design, rather than added as a standalone automation layer. Identify AI opportunities across workflows, decision logic, dashboards, copilots, agents, recommendation engines and human-in-the-loop controls. Translate business challenges into AI-enabled process concepts, user stories, capability requirements and scalable solution needs.
Partner with process owners and functional experts to clarify roles, decision rights, KPIs, governance points and adoption requirements. 3. Translate Business Needs into Data and AI Requirements Define business data requirements for AI use cases, including source systems, data objects, ownership, quality needs, business logic, semantic definitions and governance requirements. Partner with BI & Dataworks, IT and architecture teams to translate business needs into data product requirements, AI-ready datasets and scalable digital solution concepts.
Identify data quality, availability, ownership and governance gaps that limit AI scalability and ensure these are addressed in the transformation roadmap. Act as the bridge between business SMEs and technical teams, ensuring operational meaning is preserved in data models, AI logic, system requirements and implementation plans. 4. Drive Adoption, Scaling and Value Realization Coordinate cross-functional delivery teams, including business SMEs, data engineers, AI engineers, solution architects, IT project managers, digitalization teams, and external partners.
Build stakeholder buy-in by clearly communicating the business case, process impact, role impact, and required behavioral changes. Develop enablement materials, playbooks, communication packages, and adoption support for affected teams. Track value realization after deployment and ensure AI-enabled solutions are embedded into operational routines and management processes. Strategic Partnership with AI Strategy Lead OperationsChange Management an