How AI could accelerate energy transition

Energy demand stops In Europe, investors have pushed away from renewables, but AI could see cash flow return to the sector, while also upgrading fossil fuels.

Global electricity generation from Renewable energy sources are expected to jump by 60% in 2030which represents 45% of total electricity production, according to the International Energy Agency. barely 50% of European energy comes from renewable energy sources In 2024, the region has a robust onshore and offshore solar and wind pipeline waiting to be connected to the grid.

“The problem we have now is integrating all this variable supply into our energy markets,” Peter Osbaldstone, director of European energy and renewable energy research at Wood Mackenzie, told CNBC.

He said pressure on integration leads to pressure on prices, “which undermines the economics of investments, making the whole process of supporting a carbon-free energy mix more difficult, and more expensive for governments to bear.”

As demand for AI-driven energy grows, market watchers are looking forward to it Fossil fuels to overcome the energy bottleneck. International Energy Agency Its growth was adjusted for the period 2025-2030 Climate prediction Renewables decline by 5% compared to 2024, reflecting changing trends and policies, largely from the United States

Redeploying fossil fuel power is a “short-term crutch” that helps advance AI deployment, but “renewable energy is the only way to win in the long term,” Ajit Freeman, a partner at venture capital firm Norskin, told CNBC’s “Europe Early Edition” on Jan. 8.

“China and the United States have recognized the need for vast energy resources to power the future of AI, and this is reflected in the adoption of renewables. Taking a global perspective, renewable energy prices have fallen by more than 90%, and in 2024, 91% of new renewable energy projects will be cheaper than fossil alternatives,” Freeman said in a follow-up email.

“This shift leads to a self-reinforcing cycle: cheaper clean energy accelerates electrification, rising electrification boosts demand for storage and grid intelligence, and these improvements push down the cost of clean energy. In this way, AI can be said to accelerate the transition to renewables,” she added.

Dealing with intermittency

For Alberto Faraco, a senior analyst covering infrastructure at Morningstar DBRS, intermittency remains a fundamental issue with renewables. He told CNBC that investment needs to be made across the entire system, not just the power generation side.

“Data centers should help develop renewable energy sources, because that would push electricity prices up, but transportation will need to be developed, and battery storage will need to be developed,” he said, adding that renewable energy sources alone will not be enough to serve the stable needs of data centers.

“It would be impossible to phase out the gas right now,” Faraco said.

Nuclear energy is described as Fixed base load option for renewablesHowever, this does not take into account fluctuations in supply and demand. Nuclear power cannot be turned on and off when needed, Faraco said. “Of all fossil fuels, gas is the most efficient and cleanest,” he added.

That’s part of the reason why Wood Mackenzie expects gas – which the European Union considers a transition fuel – to remain part of the energy mix until 2060.

“There is a call that governments will make at some point: What do I do with gas generation?” said Osbaldstone. But ultimately, “the lights have to stay on.”

In order to withdraw from fossil fuels in line with climate goals, energy storage must increase. Battery costs reduced by 90% In less than 15 years, according to the IEA’s 2024 report, new chemicals for long-term storage are being developed.

However, the investment case is not clear-cut.

“If you have long-duration battery storage, their usage in a typical year is going to be very low, because you don’t have a lot of opportunities to really deploy those assets,” Osbaldston said, noting that their usage depends on the weather.

There are also price risks, since operators don’t know how much they will pay or make from storing and selling energy. “As more batteries are added to the grid, this arbitrage margin may decrease because there will be more batteries buying electricity at the low price and more batteries selling electricity at higher prices,” Faraco said.

“Double potential”

Proponents argue that AI could also serve as a critical enabler for smarter storage. Which allows for better management.

“AI-driven data analytics can improve planning, project design and operational decisions in real-time, leading to reduced fuel consumption, lower CO2 emissions and longer asset life,” according to a report by the International Energy Agency.

The European Commission is betting on such gains across the entire energy system in what it calls “the dual potential of energy in AI and AI in energy.”

When contacted about the bloc’s upcoming roadmap on digitalization and artificial intelligence in the energy sector, a Commission spokesperson said it would “accelerate the uptake of digitalization and artificial intelligence in the energy sector while improving energy efficiency and system reliability.” Roll back climate policy To feed the growing electricity demand from artificial intelligence and data centers.

“With the rapid advancement of AI, its potential to enhance Europe’s energy resilience and accelerate the clean transition is becoming increasingly clear. At the same time, the growing electricity needs of AI technologies require intelligent and forward-looking planning,” they said.

“The European Commission aims to ensure that the EU is fully prepared to seize these opportunities while maintaining the stability and reliability of Europe’s energy system.”

“Tremendous opportunity,” Aqeeq echoed.

“Right now, there are many examples of companies using AI to improve energy systems – Vind AI revolutionizing wind energy, Granular Energy enabling greater transparency, and Juna.ai in manufacturing,” she said, referring to startups in which Norrsken has invested.

“In addition, improving efficiency in heavy industry is one of the most powerful tools for reducing emissions. Heavy industry accounts for about a third of global energy consumption, and AI-driven optimization is now pushing industrial efficiency forward for decades.”