Applying Product Management, Systems Engineering, and AI in Utility Environments: A Practical Workshop

Utilities are navigating an increasingly complex landscape—decarbonization, digitization, customer demands, and regulatory shifts. This course introduces a practical, hands-on framework for solving these challenges by integrating Product Management, Systems Engineering, and Artificial Intelligence (AI) into real-world utility environments.

Instead of a traditional lecture format, participants will work through a real use case selected in collaboration with the utility, learning to apply SPDe-Thinking™—a convergence of Systems, Product, and Design Thinking—while leveraging AI tools and practices to improve speed, accuracy, and decision-making in solution delivery.

Participants will explore how to use AI for requirement generation, architecture traceability, stakeholder alignment, and product strategy modeling—accelerating adoption and innovation across utility systems and customer-facing products.

Who Should Attend

  • Utility Professionals involved in:

    • Capital Program Delivery

    • AMI / Grid Modernization / DER Integration

    • Smart City / Grid-Interactive Efficient Buildings (GEB)

    • SCADA, OMS, MDMS, EMS, and IT/OT Systems

  • Product Managers / Technical Leads in utility or vendor ecosystems

  • Systems Engineers / Architects designing grid tech or smart infrastructure

  • Program / Project Managers managing complex tech deployments

  • Innovation / Strategy Teams driving AI and digital transformation

  • ISO / Regulatory Professionals interested in outcome-based planning and AI integration

 

Learning Objectives

By the end of the course, participants will:

  1. Understand how Product Management principles accelerate innovation in utility solutions.

  2. Learn to apply Systems Engineering tools to manage complexity and traceability.

  3. Use the SPDe-Thinking™ framework to guide solution development in real-world use cases.

  4. Explore how AI tools can enhance product management and systems engineering—including requirements generation, stakeholder mapping, and risk assessment.

  5. Define value-driven system and user requirements rooted in utility customer outcomes.

  6. Build solution architecture maps, traceability matrices, and product roadmaps supported by AI-augmented tools.

  7. Shift from project thinking to product lifecycle management, supported by digital workflows.

  8. Leave with reusable templates and AI toolkits to apply immediately in their organizations.

Course Format & Agenda (6 Hours)

Format Highlights

  • Interactive Workshop: Minimal slides, max engagement

  • Real Use Case: Utility selects or approves a relevant business challenge

  • AI Integration: Demonstrations and guided use of AI tools (e.g., ChatGPT, Notion AI, or domain-specific platforms) to accelerate product and system practices

  • Tools Provided: Templates for use case analysis, product canvas, system requirement traceability, AI prompts, and SPDe journey map using Miro

  • Breakouts & Coaching: Cross-functional collaboration + live mentorship

Registration & Materials

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Spectrum Considerations for Utilities