AI reshapes wind turbine blade recycling

AI is becoming a central tool in wind turbine blade recycling as rapid renewable energy expansion increases pressure on end-of-life infrastructure. The wind sector added 72.2 gigawatts of new capacity in the first half of 2025, a 64% year-on-year growth rate that is accelerating demand for sustainable blade disposal and materials recovery.

Robotic inspection systems using 360-degree cameras and computer vision are addressing the difficulty of assessing blades longer than 50 meters, where manual methods are impractical. Other emerging approaches include digital twin technology for decommissioning planning, machine learning models for predicting post-recycling material properties, automated sorting and microwave-assisted pyrolysis.

Public funding and regulation are helping push the market forward. The U.S. Department of Energy’s $5.1 million Wind Turbine Recycling Prize program backed six breakthrough technologies, while Europe’s EoLO Hubs project secured $12 million in Horizon Europe funding. Companies including Fairmat, Aerones, GE Vernova, Vestas, ACCIONA, Vind AI and BladeBUG are developing AI-integrated approaches, with Fairmat securing $55.7 million in Series B funding and Aerones raising $62 million for U.S. expansion.