Masdar, Abu Dhabi’s Future Energy Company, has teamed up with Presight to create an AI-powered asset management tool for its global renewable energy projects. This tool will shift Masdar’s operations from a reactive to a predictive model, analyzing vast data from its assets to boost efficiency, prevent failures, and reduce downtime.

“With our history of developing projects using cutting-edge clean energy technologies, it was a natural progression for Masdar to explore the potential for deploying AI across energy systems to enhance efficiency and deliver data-driven decision-making,” said Mohamed Jameel Al Ramahi, CEO of Masdar.

He emphasized that integrating AI into energy systems presents a “game-changing economic opportunity,” accelerating the transition to a low-carbon future. AI’s transformative role in the energy sector is expected to enhance efficiency, optimize operations, and provide predictive analytics to improve grid resilience. Experts project AI could contribute $7 trillion to the global economy over the next decade by driving energy efficiency and substantially cutting emissions.

Masdar, co-owned by TAQA, ADNOC, and Mubadala, has invested in renewable projects globally, with a total capacity of about 20 GW and a value surpassing $30 billion. Europe is expected to play a key role in helping the company achieve its ambitious target of 100 GW of renewable energy capacity by 2030.

In recent months, Masdar has made notable strides in the green energy sector, including a $1.4 billion agreement to acquire Saeta Yield, a renewable energy firm from Canada’s Brookfield, marking its second major transaction in Spain. This follows Masdar’s earlier $889 million deal to acquire a minority stake in 48 solar plants operated by Endesa, a subsidiary of Italy’s Enel.

Earlier this year, Masdar secured a 49% stake in the UK’s Dogger Bank South offshore wind farm from RWE, highlighting its commitment to renewable energy. This venture is valued at $13.9 billion and is part of the world’s largest offshore wind farm project.