Artificial Intelligence for Utilities

Artificial intelligence is transforming how utilities plan, operate, and secure the grid. As utilities face challenges from unprecedented load growth to aging infrastructure, cybersecurity threats, and increasing operational complexity, AI is emerging as a powerful tool for improving reliability and resilience.

The AI for Utilities Summit brings together utility leaders and industry experts to share strategies and real-world applications of AI across utility operations. Through case studies and implementation-focused sessions, attendees will hear how AI is being used to modernize the grid, optimize asset performance, enhance forecasting, strengthen cybersecurity, accelerate planning processes, and support DER integration.

Register now to gain actionable insights, discover emerging best practices, and learn how your organization can successfully leverage AI to build a smarter, more resilient utility.

• Analyze the evolving regulatory landscape for artificial intelligence in utilities and evaluate approaches for responsible AI governance, compliance, and risk management
• Examine how generative AI, and agentic AI technologies can be applied to improve utility workflows, decision-making, and organizational knowledge management
• Assess the role of AI in grid modernization initiatives and evaluate applications that enhance operational efficiency, renewable energy integration, asset management, and situational awareness
• Apply AI-driven predictive maintenance and asset intelligence concepts to identify opportunities for improving asset performance, reliability, and maintenance planning
• Analyze cybersecurity risks associated with AI-enabled utility environments and evaluate the use of AI and machine learning technologies for threat detection, mitigation, and infrastructure protection
• Evaluate AI-based forecasting, optimization, and analytics tools that support renewable energy integration, DER management, and energy market operations
• Examine AI applications for DER adoption, customer engagement, and grid orchestration and assess their potential impact on utility operations and customer outcomes
• Analyze the use of AI-powered forecasting, modeling, and optimization techniques to support energy planning, resource management, and microgrid development
• Evaluate the capabilities of AI digital twins, physics-informed AI, and intelligent agents to automate planning processes, improve simulation accuracy, and accelerate interconnection studies
• Differentiate between emerging AI technologies and use cases and assess their applicability to utility operations, planning, cybersecurity, and grid management functions
• Formulate strategies for identifying and prioritizing AI opportunities that align with organizational objectives, operational challenges, and business goals
• Evaluate lessons learned from utility AI deployments and determine best practices for implementing AI solutions that improve reliability, resilience, and operational performance