Artificial Intelligences Energy Paradox 2025

Some of the identified key barriers to deploying AI solutions for energy sustainability are outlined in Table 6. These include issues around policy alignment, industry collaboration and operational and technical issues.Note: Further research is needed to differentiate solutions that can be scaled versus deployed at company level. A snapshot of cross-industry AI solutions and projects being deployed by global companies (continued)FIGURE 6 Gains achieved: Collaborative innovation projects launched, streamlined supply chains, enhanced dialogue on policy alignment Example solutions: AKER – supply chain alliances Moeve – industrial partnerships European technology company collaboration with international organization – digital transformation collaboration project in AfricaAI-driven partnerships and ecosystem collaboration Digital transformation collaboration in Africa Gains achieved: Enhanced grid stability, efficient energy storage, smart grid management, proactive maintenance planning Example solutions: US tech company collaboration with European utility – real-time grid dispatch in Europe Sample services from respective European advanced energy solutions companies – battery storage optimization, digital twin AI predictive maintenance for renewables and batteries Southern Company – grid modernization European tech and energy company collaboration – energy efficiencies achieved with global thermal generation European engineering and construction company – grid modernization in EuropeDigital transformation and AI for smart grids and power systems 50% energy company savings through real time data access Gains achieved: Support for net-zero ambitions, research insights and enhanced stakeholder dialogue to align on decarbonization strategies and global policy Example solutions: Loughborough University – researched decarbonization tool GEIDCO – multistakeholder policy research and dialogue activities with industry, international organizations, universities and governmentRelevant policy and decision-making tools Digital decarbonization assessment tool researched Note: Further research is needed to differentiate solutions that can be scaled versus deployed at company level. 19 Artificial Intelligence’s Energy Paradox: Balancing Challenges and Opportunities