Artificial intelligence-driven applications are changing the way the energy industry operates, even if the speed of that change varies between and within organisations. For a snapshot of progress in deploying the technology, a look at feedback from energy industry AI pioneer SLB and some of the other big oilfield services firms during the first quarter 2026 results season is a good place to start.
The overriding message is that AI deployment is allowing the big players like SLB, Baker Hughes, Halliburton and Weatherford to help their customers make useful, but incremental gains over the long-term rather than revolutionising their operational models. AI-driven applications are also proving most popular for their ability to make efficiency gains, rather than to boost production, at a time when global geopolitical uncertainties are affecting energy supply and demand.
SLB, the only big oilfield services firm to have established a standalone digital division, said its AI and digital services have played a crucial role in helping to offset operational headwinds in the Middle East. The Houston-based firm reported a 9% year-on-year rise in revenue from its digital division in its first quarter results, growth that the company attributed to growing enthusiasm from customers now getting a clearer picture of how AI and digital products can improve performance and efficiency.
Olivier Le Peuch, SLB’s CEO, acknowledged that its digital business still accounted for a relatively small portion of the company’s revenues, but said its impact extended well beyond its size. He told analysts on an earnings call that SLB’s approach was grounded in domain expertise, integrating AI, data and software into its platform and workflows.
“This is not about standalone tools, it’s about embedding intelligence across the full lifecycle of reservoir development and production,” he said.
The firm’s AI-driven drilling automation and advisory solution, DrillOps, is becoming increasingly widely used in Middle Eastern countries, such as Qatar and Oman, as Middle Eastern countries seek to beef up the use of digital solutions in the energy sector.
Last year, SLB said it was partnering with AIQ to support the Abu Dhabi-based firm’s deployment of its ENERGYai agentic AI technology across ADNOC’s subsurface operations supported by SLB’s Lumi data and AI platform. Lumi is also being deployed as an enterprise solution across the assets of India’s ONGC as a foundation for advanced analytics and AI‑enabled workflows. SLB has also collaborated with Petronas to further the Malaysian energy firm’s digital transformation.
In midstream, SLB is also delivering a production data management system for the East Africa Crude Oil Pipeline, the world’s longest electrically heated crude oil pipeline, which runs from the oilfields of Uganda to the Tanzanian coast. SLB will deploy its Avocet production operations software platform to collect, analyse and securely store production data, including a mobile interface to enable real-time volumetric tracking and production optimization across the oilfields.
US unconventionals
SLB has also recently bolstered its presence in the US shale sector, agreeing to acquire the upstream geoscience and petroleum engineering software portfolio of S&P Global’s energy division – a move that expands its digital subsurface capabilities and presence in U.S. unconventional workflows.
Against the backdrop of continuing uncertainties over demand from oil and gas drillers, some oilfield services firms have also been tailoring their expertise and technology for use in the booming data centre and data processing sector. It is reaping rewards, as demonstrated by 45% year-on-year growth in SLB’s data centre solutions business.
In an effort to add momentum, SLB said in March it was expanding its longstanding collaboration with US chip producer NVIDIA on the design of modular AI data centers and work with NVIDIA to create a so-called “AI Factory for Energy”, an AI-driven platform that will allow hydrocarbons producers and power firms to process and analyse large volumes of operational data.
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