As demand for artificial intelligence grows, its impact on the energy industry also grows exponentially. The data centers that power AI, cloud software and other tech advances require a significant amount of power — far more than is currently being generated by the energy industry.
In fact, AI is expected to drive a 160% increase in energy demand from data centers, and some experts predict AI could be responsible for one quarter of power consumption in the United States by 2030.
I discussed these emerging trends with Dr. Maksim Sonin, a thought leader in the energy sector and a Hydrogen Projects Fellow at Stanford University. He explained that while AI is driving the need to produce more energy faster, more reliably and with fewer carbon emissions, it can also play a role as a technological disruptor that enables these results.
AI’s Potential In Developing Emissions-Reducing Technology
The rise in energy use linked to AI comes at the same time that the scientific consensus is that the ability to limit global warming to 1.5 degrees Celsius has narrowed and become increasingly challenging. Despite this, maintaining such a goal is not yet out of reach, in part thanks to the growth and development of energy tech.
According to Dr. Sonin, the development of new technology is pivotal in reducing climate emissions, and it can (and should) be expedited with the help of AI.
“Ammonia production still relies on the Haber-Bosch process, which is over 100 years old. This is just one example of an area where there is space for disruption — and AI can prove key in helping us find these opportunities. We need AI to speed up this development because the energy industry as a whole tends to be very risk averse, which means it can take over 10 years for breakthroughs to become commercially available. Working with AI can help us identify, test and implement potential innovations much faster.”
From creating new materials to identifying catalysts for chemical reactions, Dr. Sonin views AI as a key tool in advancing technology that will help reduce emissions across the energy sector.
AI and Facilities Scaling
As valuable as the development of new technology can be, one of the biggest challenges the industry faces is enabling and scaling facilities. This is an area where Dr. Sonin sees AI as having an even greater impact.
“Scaling is simply the idea of making things bigger — such as being able to use one large compressor instead of two — to cut emissions and costs. When done right, scaling can address up to 65% of emissions and reduce capital expenditures by up to 30% to deliver global savings of up to $150 billion. The ability to accelerate industrial plants’ delivery schedules by 25% can also shave 12 to 18 months off typical project timelines.”
As Dr. Sonin’s example shows, scaling energy tech may be the most impactful way to ensure sustainable energy goals are met — and AI can play a central role in delivering more rapid and efficient growth.
“It is next to impossible to prototype at scale, but AI can help us do that through improved facilities design, predictions and modeling,” Dr. Sonin explains. “We need to run through different simulations before taking a new facility full-scale. Building a first-of-its-kind industrial unit at scale could cost several billion dollars. In other cases, already commissioned facilities experience massive production issues even though initial engineering and analysis looked sound. AI can help us improve the odds of success by rapidly running through performance models and more so we can scale with confidence.”
Improving Productivity
Dr. Sonin also expects that AI will be able to address a variety of productivity issues currently facing the energy sector. “Labor productivity has been and is expected to be an issue in 2025 and beyond, but as AI gains momentum, I expect that it will lead to gradual improvements,” he predicts.
“Even just a 10% increase in productivity can reduce capital costs by 4% or more. Improved productivity can be especially important in project management, where AI can help with de-risking, coordination and optimization to prevent engineering mistakes and delays on site.”
Dr. Sonin feels this enhanced productivity is especially important in light of current construction backlogs, which otherwise limit the ability to develop new facilities. AI can be a major factor in addressing these issues.
A Multifaceted Relationship
Ultimately, Dr. Sonin is very enthusiastic regarding AI and the energy industry, in large part because of its impact on decision-makers: “The rapid pace of AI disruption has helped change the perspectives of countless people in many industries about what we can achieve with technology.
“This helps set the perfect precedent for conservative decision-makers to change their minds. With changing mindsets and the assistance of AI technologies, we can pursue and implement new tech faster so the energy sector can get to where it needs to be. Although it will undoubtedly increase global energy demands in the coming years, AI will also become an integral part of the solution for disrupting and improving the energy industry as a whole. Therefore, I would encourage more founders and corporate leaders to explore this space deeply so we can reach our full potential.”
