How AI could accelerate energy transition
Stalling demand for energy in Europe has driven investors away from renewables, but AI could see cash flow return to the sector and also revive fossil fuels.
Global electricity production renewable energy expected to increase by 60% in 2030According to the International Energy Agency, it accounts for 45% of total electricity production. Almost 50 percent of Europe’s electricity came from renewable sources There is a strong solar energy and onshore and offshore wind pipeline in the region waiting to be connected to the grid in 2024.
“The problem we have now is integrating all this variable supply into our energy markets,” Peter Osbaldstone, Wood Mackenzie’s European energy and renewable energy research director, told CNBC.
He said pressure on integration led to pressure on prices, which undermined investment economics, making the process of supporting a decarbonised energy mix more difficult and more expensive for governments.
As AI-driven energy demand increases, market observers are turning to fossil fuels to overcome the energy bottleneck. IEA revised 2025-2030 growth to guess There was a 5% decrease in renewable resources compared to 2024; This reflects changing sentiment and policy, largely coming from the United States
Reusing fossil fuel energy is a “short-term boost” to help AI spread, but “the only way to win in the long run is with renewable energy,” Agate Freimane, partner at venture capital firm Norrsken, told CNBC’s “Europe Early Edition” on Jan. 8.
“China and the US have recognized that vast energy resources are needed to power the future of AI, and this is reflected in the adoption of renewable energy sources. From a global perspective, renewable energy prices have fallen by more than 90%, and in 2024, 91% of new renewable projects were cheaper than fossil alternatives,” Freimane said in a follow-up email.
“This shift triggers a self-reinforcing cycle: Cheaper clean energy accelerates electrification, increased electrification drives demand for storage and grid intelligence, and these improvements further reduce the cost of clean energy. In this way, it can be argued that AI is accelerating the transition to renewables,” he added.
coping with intermittency
Interruption is still a key issue with renewables, according to Alberto Faraco, senior analyst covering infrastructure at Morningstar DBRS. In his statement to CNBC, he said that investments should be made in the entire system, not just the side that produces energy.
“Data centers should help develop renewable energy sources because that will increase the price of electricity, but transmission will need to be improved, battery storage will need to be developed,” he said, adding that renewable energy alone will not be enough to meet the stable needs of data centers.
“Phasing out the gas is impossible for now,” Faraco said.
Nuclear power has been touted as a stable baseload option for renewables, but this does not account for variability in supply and demand. Nuclear can’t be turned on and off as needed, Faraco said. “Of all fossil fuels, gas is the most efficient and clean,” he added.
This is one of the reasons why Wood Mackenzie expects gas, which is considered a transition fuel by the European Union, will remain part of the energy mix until 2060.
“There is a call that governments have to make at some point: What do I do with gas production?” But ultimately “the lights must stay on,” Osbaldstone said.
In order to move away from fossil fuels in line with climate goals, energy storage needs to be increased. Battery costs dropped by 90% According to the 2024 IEA report, this will be possible in less than 15 years, and newer chemicals are being developed for long-term storage.
However, the investment situation is not clear.
“If you have long-term battery storage, its usage in a typical year is going to be very low because you’re not going to have a lot of opportunities to really deploy that asset,” Osbaldstone said, noting that their usage depends on the weather. he said.
There is also price risk, given that operators do not know how much they will pay or earn from storing and selling energy. “As we add more batteries to the grid, this arbitrage margin may narrow because more batteries will buy electricity at lower prices and more batteries will sell electricity at higher prices,” Faraco said.
‘twin potential’
Proponents argue that AI can also serve as a critical enabler of smarter storage. allow better management.
“AI-enabled data analytics can improve planning, project design and real-time operational decisions, resulting in reduced fuel consumption, reduced CO2 emissions and extended asset life,” according to the IEA report.
The European Commission believes such gains will be made across the entire energy system with what it calls “AI for energy and AI for energy.”
The bloc’s upcoming roadmap for digitalisation and artificial intelligence in the energy sector will “accelerate the uptake of digitalisation and artificial intelligence in the energy sector while improving energy efficiency and system reliability”, a Commission spokesman said, as it approaches a rollback of climate policy to fuel rising demand for electricity from artificial intelligence and data centres.
“As AI advances rapidly, its potential to strengthen Europe’s energy resilience and accelerate the clean transition becomes increasingly clear. At the same time, the growing electricity needs of AI technologies require smart, forward-looking planning,” they said.
“The European Commission aims to ensure that the EU is fully prepared to seize these opportunities, while preserving the stability and reliability of the European energy system.”
Agate reiterated the “great opportunity”.
“Apparently, there are several examples of companies using AI to improve energy systems: Vind AI revolutionizing wind energy, Granular Energy providing greater transparency, and Juna.ai in manufacturing,” he said, pointing to start-ups in which Norrsken has invested.
“Additionally, improving efficiency in heavy industry is one of the most powerful levers for reducing emissions. Heavy industry accounts for approximately one-third of global energy consumption, and AI-driven optimization now advances industrial efficiency by decades.”
