Generative AI Bootcamp – Utilities

Immersive bootcamp for utility professionals across IT, OT, engineering, and operations to leverage Generative AI across grid, assets, and customer experience while ensuring compliance, cybersecurity, and safety standards.

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There are currently no scheduled classes for this course.

Overview

  • This immersive bootcamp equips utility professionals (IT, OT, engineering, grid operations, 
  • customer service, and analytics teams) with the knowledge and guardrails to safely and 
  • effectively leverage Generative AI in a highly regulated environment.
  • Participants will learn how to apply GenAI across grid operations, asset management, customer 
  • experience, outage management, and regulatory compliance, while adhering to NERC CIP, data 
  • privacy, cybersecurity, and operational safety standards.

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Full course details

Course outline

Module 1: GenAI 101 for Utilities

• LLM fundamentals (transformers, context, hallucinations)

• Utilities-specific use cases:

o Grid load forecasting

o Outage prediction and restoration support

o Asset maintenance insights (predictive maintenance)

o Customer service automation (billing, outage inquiries)

o Regulatory reporting automation

• Risks: grid reliability, safety, cybersecurity, data exposure

Hands-on Lab: Identify 5 high-value use cases (e.g., outage management, asset monitoring); 

classify by risk, regulatory impact, and ROI

Module 2: Governance, Compliance & Security

• NERC CIP compliance considerations

• Data privacy (customer data, smart meter data)

• Cybersecurity risks in critical infrastructure

• AI governance frameworks (model risk, auditability)

Workshop: Create a Utility AI Governance Framework including:

• Allowed/blocked use cases

• Data classification policies

• Human-in-the-loop controls

Module 3: Prompt Engineering & Operational Decision Support

• Prompt design for operational scenarios

• AI-assisted troubleshooting and incident response

• “Human + AI” collaboration for grid operators

Lab: Use prompts to:

• Analyze outage scenarios

• Generate restoration plans

• Summarize field reports

Module 4: AI for Engineering & Development (Copilot / Automation)

• AI-assisted coding for utility systems (SCADA integrations, APIs)

• Documentation automation for compliance and audits

• Code modernization (legacy systems → cloud)

Lab: Generate:

• API service for outage reporting

• Unit tests and documentation using AI tools

Module 5: AI in the Utility SDLC & DevOps

• Integrating AI into:

o Requirements (use case modeling)

o Development (code generation)

o Testing (automation)

o Deployment (CI/CD pipelines)

• Ensuring traceability for regulated environments

Lab: Use AI to:

• Convert requirements into test cases and code

• Track outputs for compliance and audit

Module 6: Testing, QA & Reliability

• AI-assisted test generation (functional, regression, edge cases)

• Testing critical infrastructure systems

• Reliability and resilience testing

Lab: Generate and execute:

• Test scenarios for outage management systems

• Performance and reliability validation

Module 7: DevOps, Observability & Grid Reliability

• AI-enhanced monitoring and alerting

• Predictive anomaly detection in grid systems

• Incident management with AI insights

Lab: Simulate:

• Grid anomaly detection

• AI-driven root cause analysis

Module 8: Data, RAG & Smart Grid Intelligence

• Using Retrieval-Augmented Generation (RAG) with:

o Asset data

o GIS systems

o Smart meter data

• Secure data access and governance

Lab: Build a RAG-based assistant for:

• Asset maintenance queries

• Field technician support

Module 9: Adoption Roadmap & Metrics

Audience / prerequisites

This course is intended for professionals in roles such as:

  • Project Managers / Scrum Masters
  • Product Owners / Product Managers
  • Business Analysts
  • Developers / Engineers
  • IT, Operations, or Transformation professionals
In this class you will learn how to

• Explain how LLMs work and where GenAI adds value in utilities operations and digital 

transformation

• Apply AI-assisted workflows across asset management, outage response, customer 

service, and grid analytics

• Use prompt engineering and AI tools to accelerate development, testing, and operational 

decision-making

• Integrate AI into SDLC, DevOps, and operational systems (IT/OT convergence)

• Implement governance, compliance, and cybersecurity controls (NERC CIP, data 

protection, critical infrastructure security)

• Define KPIs and rollout strategies for enterprise AI adoption in utilities

Generative AI Bootcamp - Utilities Schedule

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There are currently no scheduled classes for this course.

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