Can Quantum Computing Tame AI's Energy Appetite?

The U.S. Department of Energy has launched the Quantum Genesis Q Competition and is offering up to $215 million in funding to speed development of fault-tolerant quantum computers. The competition is soliciting proposals aimed at deploying machines with at least 100 logical qubits that can execute hundreds of millions of fault-tolerant operations and run scientific demonstration programs. Separately, the DoE issued a lab call asking national laboratories to develop tools and expertise to verify performance of such fault-tolerant quantum systems. DoE Undersecretary for Science Darío Gil framed the competition as a way to bring commercial sector involvement through both collaboration and competition, with the broader goal of positioning the United States as a leader in the global quantum race. The verification-focused lab call intends to create a testbed to validate that machines meet the performance and fault-tolerance standards laid out in the competition. Interest in these programs is partly driven by the energy implications of large-scale computing. A preview of a BCG Institute report reported by Semafor suggests mature quantum computing could help address 20 to 40 percent of emissions in hard-to-abate sectors such as steelmaking and cement production, and could be applied to carbon capture, green hydrogen, ammonia, and batteries. The report also estimated that quantum computing’s own carbon footprint would be relatively small compared with the energy demands of the AI industry because quantum is likely to be used for targeted problems rather than as a general-purpose compute layer. Industry proponents argue quantum could also reduce the energy intensity of AI workflows. Peter Chapman, president and CEO of IonQ, is quoted as saying that for certain AI tasks quantum processors will outperform GPUs on both performance and energy efficiency, an assertion he made in a 2024 Forbes interview cited by the source. Researchers are also exploring quantum-enabled advances in energy technologies — from proposed quantum batteries to methods for harvesting waste heat and electronic designs that minimize transmission loss — which supporters say could further improve efficiency across computing and industry.