What artificial intelligence is doing to the energy industry right now is every bit as interesting as what the energy industry is doing with AI.
Oil and gas service companies gain from both sides of the equation. They’re raking in money from power-related demand while rolling out their own AI-based tools.
Meanwhile, oil majors and other large energy companies are scrambling to integrate AI into all parts of their operations, reshaping their businesses in the process.
Data Centers’ Energy Gluttony
Demand for AI-related data centers has brought a windfall to service companies that sell gas turbines and grid systems. The International Energy Agency laid out the scale of the market in its just-released 2025 World Energy Outlook.
“Global investment in data centers is expected to reach $580 billion in 2025. Those who say that data is the new oil will note that this surpasses the $540 billion being spent on global oil supply – a striking example of the changing nature of modern economies,” noted IEA Executive Director Faith Birol.
Repeat: This year the world will probably spend more money developing AI data centers than developing oil production.
Baker Hughes reported that its Industrial and Energy Technology segment, which includes power generation and LNG, gained almost $11 billion of new orders in the first three quarters of 2025, lifting backlog to $32.1 billion.
As the Australians say: Crikey!
Everybody seems to want in on this AI datacenter play. In October, Halliburton announced a strategic collaboration with energy solutions provider VoltaGrid, focused on delivering distributed power generation for data centers worldwide.
SLB’s agentic AI Tela is embedded in its Petrel software. Image courtesy of SLB.
ExxonMobil has unveiled plans to equip data centers with natural gas power plants combined with carbon capture and storage systems. In November, Chevron identified West Texas as the location for its first natural gas power-plant project to support data center needs, targeting 2027 for startup.
Major oil companies even have a side hustle in this gig – direct liquid cooling for the immense heat generated by data center computers. Shell, BP and other big oil companies are now offering liquid-based cooling solutions specifically designed for data center requirements.
In June, Shell introduced its new data center coolant Shell DLC Fluid S3, a name that pretty much screams “secret ingredient” – although, the company did describe it as a propylene glycol-based liquid.
“Data center growth is reshaping North America’s power landscape faster than grid and policy systems can adapt,” observed research and analysis company Rystad Energy in a recent report.
“Energy companies that deliver quick, innovative and cost-effective solutions will benefit most. Over time, carbon capture, storage and renewable integration will be key to sustaining this growth in a decarbonizing world,” it noted.
SLB, the company formerly known as Schlumberger, has created a standalone Digital division and now reports its revenues as a separate business unit. Earlier this year, analysts at U.S. Bancorp estimated the division could be worth between 10 and 25 percent of SLB’s total enterprise value.
CEO Oliver Le Peuch said SLB saw “strong growth in our Data Center Solutions business, extending our reach with hyperscalers to a new market.”
“Hyperscalers” are companies that operate large data centers offering massive computing power and data storage. The name comes from their ability to scale up computing power on demand.
“Digital continues to transform the oil and gas industry, and this has been our fastest-growing business in recent years. We have been on a long journey to digitize the oilfield – from modeling and planning to operations and automation,” Le Peuch said.
Integrating AI and Oilfield Service Software
Also in October, SLB introduced its new agentic AI assistant called “Tela” and launched its AI-powered Production System Optimization (AiPSO) platform with ADNOC in Abu Dhabi.
“Tela doesn’t just automate tasks – it SLB’s agentic AI Tela is embedded in its Petrel software. Image courtesy of SLB. t From previous page Vol. 46 • No. 12 • December 2025 19 can understand goals, make decisions and take action. It’s the convergence of 100 years of domain science and cutting-edge digital technology,” said Rakesh Jaggi, SLB’s president of digital and Integration.
Service companies frequently tout two features of their AI tools. First, those tools can operate as “answer machines,” drawing on huge databases of stored experience and industry-relevant information. Second, they can respond to Natural Language Queries – the nontechnical language of everyday speech.
SLB has an interesting twist on this, pitching Tela’s capability as an intelligentassistant interface for its Petrel subsurface software. The company claims it provides “instant guidance with tailored help documentation and expert content for seamless learning.”
A Creeping Transformation
Hype about AI – and there’s lots of hype about AI – claims that new AI tools are revolutionizing oil and gas operations. But in reality, artificial intelligence has been gradually seeping its way into all parts of the energy business. It’s brought more of an ongoing transformation than a sudden and revolutionary makeover.
In a recent posting, BP outlined five ways it deploys AI and other new technology to improve performance:
- Optimizing oil and gas drilling: Using technology at the company’s Houstonbased high performance computing center, BP determines optimal drilling paths in places like the Gulf’s U.S. waters and the Permian Basin. AI evaluates geological data “to determine the best and safest drilling trajectories, cutting what used to be a months-long process down to just days,” BP reported.
- Digital modeling: Also known as “digital twins,” BP’s virtual models can be viewed anywhere with online access. Twinning uses laser-scan technology and machine learning to collect data and help prioritize areas for attention.
- Improving onshore efficiency: BPX Energy, BP’s onshore oil and gas business in the U.S., uses AI to increase efficiency. It is piloting AI-generated morning reports with key production insights to direct frontline work.
- Faster data analysis: BP partners with companies that specialize in developing software for data analysis and intelligence. Company teams are exploring the use of AI technology to interpret information rapidly and deliver insights directly to frontline operators.
- Preventing disruptions: Like other oil companies, BP uses machine learning tools to detect and predict issues with its offshore production equipment. The system warns about potential problems and helps workers proactively address issues before they escalate, reducing production challenges and interruptions.
Oil and gas companies now are looking for measurable improvements from AI tools – in data analysis, in drilling and development efficiency, in enhanced production, in reduced accidents and downtime.
Despite all the hype and the talk about an AI revolution, they’re focused more on bread-and-butter AI applications in daily operations, and less on digital pie in the sky.