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AI efficiency gains come at a high energy cost<br>Technology is tackling complexities that have held back progress in cutting energy waste

Gamechanger: AI can analyse vast amounts of data and make efficiency adjustments © Getty Images

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Sarah Murray

PublishedJune 15 2026

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Former US energy secretary Steven Chu once described energy efficiency as “not just low-hanging fruit” but “fruit that is lying on the ground”. Yet despite being cost-effective, this critical method of decarbonisation is widely underused.<br>The process of identifying where and how energy is wasted is complex and time-consuming, which is why technologies and management practices in this area are not adopted as widely as they could be. Artificial intelligence could now be changing that.<br>“AI can understand where the problems are and where the waste is — and you don’t need five people with PhDs looking at monitors all day,” says Brian Motherway, head of energy efficiency at the International Energy Agency.<br>In large factories with thousands of motors, valves and other pieces of equipment, for instance, AI can analyse everything and make efficiency adjustments. “It’s beyond the power of anyone to handle all that data,” he says.<br>A boost is badly needed. IEA data shows that the rate of progress towards global efficiency targets is slowing, particularly in industry. “In some ways that’s surprising because it’s where the financial case is clearest,” says Motherway.<br>However, he says, barriers to energy efficiency adoption should not be underestimated: “Maybe the CEO loves the idea of cutting ribbons on solar-panelled roofs but it’s hard to get excited about a boiler.”<br>Maybe the CEO loves the idea of cutting ribbons on solar-panelled roofs but it’s hard to get excited about a boiler

Energy efficiency investments produce results less rapidly and less visibly than shifting to renewable energy sources, says César Quilodrán-Casas, an advanced research fellow in machine learning at the Grantham Institute for Climate Change and the Environment at Imperial College London. “It’s not such a big story to tell.”<br>Meanwhile, increasing energy efficiency often requires equipment upgrades that can be more complex than building a wind farm or solar installation.<br>“Companies need to go factory by factory investing in bits of kit that are often bespoke,” says Sam Kimmins, director of energy at the Climate Group, a non-profit that works with companies and governments on meeting global net zero goals.<br>But if complexity is hampering progress on energy efficiency, it is something AI is effective at managing. “AI is really good when you’ve got complex and highly unpredictable data,” says Kimmins.<br>In factories and other large industrial operations, he explains, sensors attached to every piece of equipment generate large volumes of data that AI can use to identify inefficiencies in equipment or processes.<br>When it comes to physical infrastructure and the built environment, AI can be combined with digital twin technology, which creates digital representations of the real world.<br>Recommended<br>LexArtificial intelligence<br>How AI might save more energy than it soaks up<br>Premium content

Developed in the 1960s for Nasa’s spacecraft simulations, digital twin technology simulates the workings of an entire facility, enabling potential changes to be tested virtually before making physical adjustments.<br>AI expands its possibilities, as it means efficiency adjustments can be made...