Director, AI Productivity Strategy & Governance

EmersonCranberry Township, PA

About The Position

Emerson is seeking a Director of AI Productivity Strategy & Governance to lead the strategy, prioritization, governance, and adoption of AI-enabled productivity initiatives. This role involves partnering closely with the executive owner of AI Productivity and Operations Performance to translate business priorities into a disciplined, responsible, and value-driven AI productivity portfolio. The position acts as a central connector across business, technology, and risk partners to ensure AI productivity initiatives are scalable, secure, and measurable from idea to adoption.

Requirements

  • Bachelor’s degree in business, operations, engineering, information systems, data analytics, computer science, or a related field, or equivalent combination of education and experience
  • Minimum of 8 years’ experience with operations, strategy, transformation, process improvement, digital enablement, analytics, portfolio management, or technology adoption
  • Minimum of 2 years’ experience working with AI, GenAI, automation, analytics, or digital productivity tools
  • Experience leading cross-functional initiatives and strategy, transformation, portfolio management, or productivity initiatives in a complex or matrixed organization
  • Demonstrated ability to establish governance frameworks, operating models, roadmaps, and executive-level reporting
  • Strong understanding of AI productivity use cases such as copilots, knowledge assistants, workflow automation, document generation, reporting automation, and decision support
  • Experience driving adoption, change management, training, or process redesign to support new ways of working
  • Strong communication skills with the ability to translate technical topics into business-relevant language

Nice To Haves

  • Master’s in business administration (MBA), Master’s degree, or relevant certification in AI, data automation, project management, or change management
  • Familiarity with enterprise AI tools and platforms such as Microsoft Copilot, generative AI assistants, RAG-based knowledge assistants, workflow automation
  • Experience with Lean, Six Sigma, process excellence, product management, portfolio management, or change management.
  • Experience partnering closely with IT, cybersecurity, legal, HR, data governance, and risk teams
  • Experience supporting productivity or operational excellence initiatives in industrial automation, engineering services, manufacturing, project execution, cybersecurity services, operations, or shared services

Responsibilities

  • Partner with senior and executive leadership to define the AI productivity vision, strategy, and multi-year roadmap aligned to business priorities.
  • Translate organizational objectives into a structured portfolio of AI use cases focused on productivity improvement, operational efficiency, decision-making, and business value.
  • Establish and lead a centralized AI productivity intake, prioritization, and portfolio management process, ensuring clarity of sponsorship, success metrics, and benefits realization.
  • Design, implement, and maintain AI governance and Responsible AI frameworks, embedding principles such as privacy, security, transparency, fairness, human oversight, and audit readiness.
  • Collaborate across business units, IT, data, cybersecurity, legal, compliance, finance, and HR to move AI initiatives from discovery through pilot, production, adoption, and value realization.
  • Lead development of business cases, ROI models, and benefit tracking to measure productivity gains, financial impact, and risk mitigation.
  • Build and execute AI adoption and change management strategies, including communication plans, training, playbooks, and enablement resources that support sustainable adoption.
  • Monitor emerging AI trends, tools, and best practices to inform strategy and continuously improve the AI productivity portfolio.
  • Facilitate AI steering committees, governance forums, and portfolio reviews, escalating risks, dependencies, and key decisions as needed.
  • Build and lead a team responsible for AI productivity governance support, adoption enablement, portfolio tracking, and value realization.
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