AI-powered vegetation management: Advancing utility risk management
Machine learning transforms vegetation management into a utility risk tool—cutting wildfire threats and improving grid resilience.
Category: AI
Strengthening AI Governance for LLMs with Semantic Context
Utilities can strengthen AI governance by applying semantic models to LLMs, unlocking accurate, trusted, and domain-specific insights.
AI Strategy for Utilities: A Value Approach
Utilities across the industry are building their AI strategy as part of broader digital transformation efforts to modernize operations, enhance customer experience, and improve grid
Smarter Utilities: Machine Learning in Meter Data Management
Machine learning enhances meter data management by reducing false positives, improving anomaly detection, and streamlining VEE for utility analytics teams.
Balancing Empathy and AI: Preserving Humanity in the Utility Analytics AI Journey
Balancing AI efficiency with empathy and proper training for teams ensures technology enhances, rather than diminishes, our humanity.
AI for Utility EOCs: A Use Case in Emergency Response
Discover how AI can transform your utility’s EOC through a proof-of-concept AI decisioning assistant for emergency response.
Top 2025 utility analytics trends transforming the industry
Advanced analytics is helping utilities tackle challenges head-on—transforming operations, improving decision-making, and creating new opportunities to adapt and excel
How RAG architecture improves knowledge base interactions
Implementing retrieval-augmented generation (RAG) architecture into knowledge bases transforms data utilization by equipping users with swift and accurate information while enabling subject matter experts to
Advance utility asset management with AI desktop inspections
Modern utilities face an array of challenges, from outdated inspection methods to maintaining an aging infrastructure. Traditional inspection methods can force inspectors to drive to
A guide for assessing your team’s Generative AI readiness
Explore the steps necessary to evolve from excitement to genuine generative AI readiness through implementations in business strategy, IT strategy, and AI governance. Generative AI