AI in the Electric Grid: Industry Perspectives on Progress, Barriers, and the Path Forward

Matt Green – TRC

As artificial intelligence begins to transform many industries, adoption has progressed more slowly among the companies responsible for planning and operating the U.S. electric grid. This presentation explores the current pace and progress of deployed AI applications across grid planning and operations, drawing on recent industry pilots, utility initiatives, and emerging research. This presentation highlights promising near-term technologies, including applications in asset analytics, AMI data insights, improved visibility into distributed energy resources, and enhancements to grid planning processes.

The discussion also examines the technical, organizational, and regulatory factors influencing adoption, including data readiness, network model fidelity, cybersecurity considerations, and utility risk tolerance. It also discusses approaches that could help reduce risk and accelerate adoption, including opportunities for greater standardization in data models, system interfaces, and validation frameworks. The session further explores how utilities, regulators, and industry stakeholders can more transparently evaluate the tradeoffs associated with AI deployment, balancing innovation with reliability, cybersecurity, and regulatory accountability.

This industry-focused perspective identifies practical opportunities and enabling conditions that could help accelerate responsible AI adoption across electric utilities while maintaining reliability, safety, and regulatory compliance.