Why the Energy Sector Needs a Smarter AI Strategy

CobyDigital Marketing2025-07-118480

Artificial intelligence is rapidly changing the world around us as our systems get smarter, and the resource and energy use of large language models grow ever larger. In the energy sector, artificial intelligence represents a double-edged sword: AI could help the sector overcome some of the hurdles involved in maintaining global energy security while we transition to cleaner alternatives, but it could also pose an existential threat to vulnerable power grids if used indiscriminately.

Artificial intelligence requires a staggering amount of energy to train and power its complex computations. Energy demand from data centers is on track to double by just 2030 as the sector explodes in growth. As a result, many world leaders are starting to see AI energy demand as an imminent threat to energy security, and are beginning to prioritize AI regulation and increasing energy production capacity.

“In the past few years, AI has gone from an academic pursuit to an industry with trillions of dollars of market capitalisation and venture capital at stake,” according to the International Energy Agency. The vast amount of energy needed to power this growth trajectory means that “the energy sector is therefore at the heart of one of the most important technological revolutions today.”

However, it’s not entirely clear exactly how much energy AI is consuming – we just know that it's a lot. The sector is extremely opaque, and governing AI is therefore a tricky situation at present. As of May 2025, a whopping 84 percent of global large language model traffic took place using AI models operating with zero environmental disclosure. And that doesn’t just include energy use – AI also has a major impact on water sources, as water is used in cooling systems for data centers as well as thermoelectric plants.

But while policy, regulation, and transparency measures remain fuzzy, global industry leaders are already busily integrating machine learning into a broad range of sectors. In the energy sector, it is being used for automation of systems for nuclear plants, and in renewables for more accurate forecasting of energy supply and demand, which will help stabilize grids as variable renewable energy sources like wind and solar become more prevalent in global energy mixes. It’s also enhancing energy storage through improved battery design, safety, and management strategies, and even futuristic innovations to give new life to dead batteries. AI is even being used to making coal mining more profitable in China.

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Clearly, global industry is off to the races to find out how AI can make their business more efficient, lest they be left behind. But a more methodical and structured approach – not to mention clearer policy and regulations – will be necessary to ensure that the technology is being used efficiently and responsibly.

“It is not uncommon for business units to get ahead of the curve by piloting or initiating proof of concepts on their own to keep up with AI advancements, states a recent Forbes report. “But, when it comes to technology and transformation, rash, siloed decision making rarely produces the intended business outcomes and is often counterproductive.”

Instead, more transparency and standardization will be critical to make sure that industry leaders aren’t wasting money and resources chasing down the same pathways – or exposing our energy systems to cyberattack. Smart tech needs to work hand-in-hand with IT to make sure that AI innovations are based in good data management and cybersecurity. “The investments needed to build that IT foundation, and ultimately to scale the [operational technology] and analytics that sit on top of it, will likely transcend business units and functional silos—and because of that, companies could need a structured way to think about them,” the Forbes report went on to say.

On the energy-production side of the equation, the public sector is facing similar challenges. The United States Department of Energy (DoE) has acknowledged that AI could be invaluable in managing smart grids capable of handling increased flows of variable energies like wind and solar, but introduces significant risks if deployed ‘naïvely.

By Haley Zaremba for Oilprice.com

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