Further evidence that artificial intelligence is having a deep impact on the operations of upstream energy companies has been provided by Rystad Energy, whose latest analysis suggests that digitalization and AI could create nearly $500bn in cumulative value for E&P companies between 2026 and 2030.
That scale of added value will come through cost reductions from more efficient operations, production increases from higher uptime and increased recovery, and compressed development timelines.
For exploration and production (E&P) companies currently investing in digital and AI, that translates into additional value of $80bn a year in 2030 compared to 2025 levels, according to the authors Jon Marsh Duesund and Andreas Bakke Moan, respectively a Partner and Project Manager in Advisory at Rystad,
Some of the industry’s major players are already reaping the benefits. Rystad cites ADNOC’s estimate that it had already achieved $500m in AI-driven value in 2023, as well as reporting from Norway’s Equinor indicating it had made around $200m in AI-related savings between 2021 and 2024, before making an estimated $130m of savings in 2025 alone.
However, progress is likely to vary across the four main workflow categories of
asset development; operations and maintenance; exploration and reservoir development; and drilling, wells and production.
For newer deployments, adoption is most rapid in operations and maintenance, mainly in the areas of predictive maintenance and remote operations, where double-digit cost reductions are being delivered at leading operators.
The authors say subsurface workflows hold the largest untapped value potential, particularly for increasing extraction volumes and cutting drilling costs. They also note several operators have reduced seismic interpretation timelines from months down to around 10 days.
“A key structural finding across all four workflow categories is that AI, in general, does not necessarily raise the ceiling for the best operators, it lifts the rest of the industry towards the performance level that the best operator already achieves,” the authors say.
That is illustrated within the US shale sector, where the biggest impact of new technologies is likely to be for averagely-performing wells rather than the best-producing wells, where output is already close to being maximised.
Following on from this, AI also makes a bigger impact on the bottom line for more complex offshore operations than for relatively straightforward onshore projects. Rystad estimates that potential savings for the most complex deepwater wells could be more than 50%, while average improvement potential for US land drilling would be closer to 10%.
Digital tools demand
This all feeds into increased demand for products benefits for digital technology providers. Rystad estimates that E&P firms could be spending $35bn a year for digital tools and services in 2030, compared to $25bn in 2025, with the annual figure set to approach $50bn by 2035.
The pace at which this new technology can be absorbed will depend on the state of readiness of a given company.
“The central barrier to capturing this value is not technology availability but deployment at scale,” the authors say.
They highlight potential bottlenecks in AI adoption, such as the speed at which organisational data silos can be broken down, acquiring enough data to train AI models, and the need for extensive reworking models so they can be transferred between assets. But they also say newer AI developments, such as improved automation using agentic AI, could help overcome these issues, allowing simpler integration and faster adoption of digital solutions.
The authors stress it is too early to be certain of how quickly these newer approaches will feed through across the industry, but say that, if their adoption does accelerate, value creation from digital initiatives could reach $150bn a year in 2030, and possibly greater than $300bn by 2035 – the latter almost double Rystad’s base case estimate.
(Photo: Shutterstock)
