One of the hottest topics of CERA week in Houston last week was the expanded use of artificial intelligence. Much of the focus has centered on AI’s power demands, with some analysts projecting that AI could use more electricity than all U.S. households by 2030. The other major topic was how AI will help meet those future energy needs. AI is already creating enormous efficiency gains and dramatically raising levels of productivity. The energy sector is no different and stands to benefit tremendously from AI’s capabilities. 

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Whether it is marginal improvements or transformative breakthroughs, there are countless ways AI will help the energy sector and consumers. Here are four topics worth following. 

1. Permitting made easier. Onerous permitting processes at every level of government have frustrated developers of all forms of energy projects. Lengthy reviews, frivolous lawsuits and ineffective coordination increase costs and prevent new energy supplies from coming online. AI is helping projects move through the permitting process faster without compromising public health or community engagement. Machine learning and AI algorithms synthesize data much faster, which provides quicker permit reviews and finds ideal siting locations. Microsoft is experimenting with AI to improve the licensing and permitting for advanced nuclear projects. AI can wade through public comments faster to address concerns while holding government agencies accountable. NEPAccess uses AI to inspect past NEPA reviews, which can provide retrospective analysis of how accurate the environmental impact assessment was and use past reviews to inform current and future projects. 
2. More energy savings for families and businesses. Energy efficiency is a win-win when driven by the private sector and individual choice. Reducing energy consumption saves families and companies money and reduces emissions from buildings. While home and building energy audits to identify savings are nothing new, AI has helped optimize building energy use based on weather, people in the building, and time of day. For instance, the managers of two buildings with 119 units in Gustavsberg, Sweden deployed AI technology to reduce energy consumption by 20 percent. So long as governments do not ration energy, AI can empower homeowners and building managers to light, heat, and cool buildings more effectively. 

3. Unlocking innovation and new energy supplies. Proponents of AI describe the potential benefits as suddenly having dozens of highly capable research assistants. Scientists, engineers and innovators at national laboratories, incubators, and private companies will have more access to data and knowledge than ever before. Like most industries, energy companies are merely scratching the surface when it comes to the potential for AI to develop better batteries, extract natural resources with more precision, or discover new materials.  At Princeton’s Plasma Physics Laboratory, scientists and researchers are using AI to help with the viability of fusion power. These advancements will lower exploration and production costs, and increase supply when domestic and global energy demand is set to steadily increase over the next several decades. AI will generate efficiency gains from raw materials to transportation to end-use consumption throughout the entire energy supply chain. 

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4. Building resiliency for the grid and extreme weather risks. In addition to bringing new energy supplies online, AI is making existing power generation run more resourcefully. Machine learning and data collection have better balanced supply and demand by predicting energy consumption patterns and scheduling power plant maintenance more efficiently. Paul Dabbar, CEO of Bohr Quantum Technology and the former Under Secretary for Science at the Department of Energy, said that these technologies will “drive up availability, making more power for cheaper cost. It’s more reliable. It’s already being deployed on certain types of power plants.”  Similar information-gathering and predictive capabilities are being used to predict extreme weather events. AI is not only more accurate than conventional weather forecasting systems, it’s much and dramatically more energy efficient. Greater accuracy in extreme weather forecasting will not only save lives but will reduce economic and environmental costs. 

The common thread for every issue is listed above efficiency.  AI requires a lot more energy, but the productivity advantages will be transformative for the energy sector. More knowledge, better data, and greater efficiency from AI will be critical to meeting the world’s energy needs and environmental goals. 

The views and opinions expressed are those of the author’s and do not necessarily reflect the official policy or position of C3.