The rapid buildout of data centers to support widespread integration of large language models in virtually every economic sector imaginable, from our energy grids to your electric toothbrush – yes, really – is pushing energy demand growth projections to unprecedented levels, threatening to far outpace energy capacity additions and imperil energy security on a global scale. On the other hand, artificial intelligence holds enormous promise for improving energy efficiency in a wide range of systems and may hold the key to unlocking next-gen clean energy methods and technologies that could be integral to enabling feasible decarbonization pathways. In the clean energy sector, artificial intelligence is being used to improve forecasting models for more sophisticated and accurate predictions of energy supply and demand, leading to greater grid stability at a time when our electricity grids have never been more stressed. These breakthroughs, and the speed that they are being achieved in, could be transformative for the deployment of next-gen clean energy. By slashing research timelines and finding materials that improve the performance and durability of clean energy infrastructure, experimental technologies that would have otherwise been prohibitively expensive to design, test, and develop can now be made scalable and commercially viable.