Director, AI Productivity Strategy & Governance

Emerson•Cranberry Township, PA

About The Position

Emerson has an exciting opportunity for a professional with experience utilizing AI to optimize productivity strategy. As the Director of AI Productivity Strategy & Governance, you will lead the strategy, prioritization, governance, and adoption of AI‑enabled productivity initiatives. You will partner 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. This role serves as a central connector across business, technology, and risk partners to ensure AI productivity initiatives move from idea to adoption in a scalable, secure, and measurable way.

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.