Case Study: AES achieves millions in cost savings and improved energy reliability with H2O.ai

AES Transforms its Energy Business with AI and H2O.ai

AES, a global energy company, needed a way to turn AI into measurable business value across wind, hydroelectric, and smart meter operations. Working with H2O.ai, AES looked to improve predictive maintenance, optimize energy bidding, and reduce wasted technician visits while increasing reliability, revenue, and ROI.

H2O.ai helped AES implement the H2O AI Cloud, along with H2O MLOps, H2O Wave, and the H2O AI AppStore, to build and deploy models across the business. The results included more than 35 wind-turbine models in production, over $1M in annual savings by eliminating 3,000 non-essential truck rolls, millions of dollars in cost savings from predictive maintenance, a 10% reduction in CAIDI from vegetation management, and a broader scale-up to 150+ models and 85 AI use cases in production.

AES

Sean Otto

Director and Head of AI