In a market update sent to Rigzone recently, Rystad Energy described digitalization and Artificial Intelligence (AI) in upstream oil and gas as “a $500 billion opportunity”.
Rystad noted in the update that, according to its estimates, digitalization and AI will create close to $500 billion in cumulative value for exploration and production companies between 2026 and 2030.
“This value is captured through cost reductions from more efficient operations, production increases from higher uptime and increased recovery, and compressed development timelines,” Rystad said in the update.
“Cost reductions and production increases are the largest value pools and contribute roughly equally through 2030,” it added.
“Exploration and production players currently investing in digital and AI are expected to capture an additional value of $80 billion per annum in 2030 compared to 2025,” it continued.
According to a chart included in its update, value creation will stand at $132 billion in 2030 alone. Back in 2025, it stood at $51 billion, the chart showed.
“Returns are already visible in the industry,” Rystad highlighted in its update.
“ADNOC reported $500 million in AI-driven value already in 2023 … [and] Norway’s Equinor generated around $200 million in AI-related savings between 2021 and 2024, before reporting $130 million in 2025 alone,” it added.
Rystad warned, however, that the trajectory is not linear.
“Digital value creation follows a compounding curve as adoption increases and organizational capabilities mature,” it pointed out.
ADNOC announced, in a statement posted on its website on March 5, 2024, that it generated $500 million (AED1.84 billion) in value by deploying AI solutions in 2023.
“Over 30 AI tools have unlocked significant value across ADNOC’s full value chain, from field operations to smarter and quicker corporate decision-making,” ADNOC said in its statement.
In a statement posted on Equinor’s website on January 7, Hege Skryseth, the company’s executive vice president for Technology, Digital, and Innovation, said, “since 2020, we have realized values of over $330 million with artificial intelligence in industrial processes, of which $130 million came in 2025”.
“We primarily use ‘traditional’ machine learning on our operational data. Our employees can use AI tools like copilots, chatbots, and agentic AI to solve tasks and work in new ways,” Skryseth added in that statement.
4 Main Categories
Rystad stated in its update that the $500 billion value creation opportunity in upstream oil and gas sits across four main workflow categories.
“The first, asset development, and second, operations and maintenance, relate to mostly surface workflows,” it highlighted.
“The third, exploration and reservoir development, and fourth, drilling, wells and production, represent subsurface-focused workflows,” it added.
Each category is at a different stage of digital maturity, according to Rystad.
“Historically, operators have deployed a wide range of digital tools into various workflows, especially within exploration and reservoir development,” it said.
“When it comes to newer deployments, operations and maintenance is seeing more rapid adoption, primarily through predictive maintenance and remote operations delivering double-digit cost reductions at leading operators,” it added.
“Subsurface workflows hold the largest untapped value potential, especially from getting more volumes out of the ground and reducing drilling costs,” it continued.
“Several operators have, for instance, compressed seismic interpretation timelines from months to around 10 days and the next step is to transfer this increased reservoir knowledge into real value,” it went on to note.
Rystad stated in its update that 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”.
Digital, AI Purchases
Rystad noted in its update that capturing the value at stake requires investment in digital tools, infrastructure, and integration.
It revealed that exploration and production companies are estimated to have spent around $25 billion on digital and AI purchases last year and said the market for providing these tools and services is expected to grow by more than $10 billion by 2030, “surpassing $35 billion in total annual market size, before growing closer to $50 billion by 2035”.
Rystad said early adopters of these technologies typically have digitalization and AI as an integral part of their strategy.
“Conversations with various industry stakeholders highlight that organizational readiness determines the realistic pace,” Rystad highlighted.
“Traditional cloud migration can take multiple years, cybersecurity gates add months, while cross-silo collaboration requires cultural shifts that no software can automate,” it added.
“Beyond adopting off the shelf solutions, some of these players seek to develop their own solutions in-house to gain a competitive advantage over the rest of the industry,” it continued.
Rystad noted, however, that “the central barrier to capturing this value is not technology availability but deployment at scale”.
“Advanced E&Ps, and those with less capabilities to start, opt for partnerships with suppliers and technology experts to reduce complexity, and simplify integration across equipment, assets, and different parts of their organization, typically through platform solutions,” Rystad said.
“Traditional oilfield service (OFS) providers with domain expertise, and technology experts such as integrators or hyperscalers are among the most important partners for E&Ps seeking to translate digital investment into operational returns,” it pointed out.
Further Than the Base Case
Rystad stated in its update that AI is accelerating the value potential of digital solutions in oil and gas.
It added, however, that, “despite many breakthroughs, most current AI applications in upstream rely on traditional machine learning models trained on equipment and workflow-specific data”.
“That training data takes years to accumulate, and models rarely transfer across assets without significant rework,” it added.
Newer AI approaches may change this dynamic though, Rystad outlined.
“For instance, through agentic AI automating tasks and augmenting humans in a way that breaks down organizational silos and acting as a contextualizing layer that functions across varied data types without full retraining, although this remains an emerging capability rather than a proven solution,” Rystad said.
“As such, we see a scenario where AI accelerates the value creation further than the base case, where breakthroughs simplify integration and compress adoption timelines industry wide,” Rystad revealed.
“In this higher scenario, annual value creation from digital initiatives reaches $150 billion already in 2030, with potential to further grow past $300 billion by 2035, compared to the base case of $178 billion in 2035,” it projected.
Rystad noted in its update that this accelerated AI scenario would also require additional spending on digital solutions, “up to $50 billion annually in 2030 and close to $80 billion by 2035”.
“This scenario would then follow the wider global trend of more money being injected into AI,” Rystad said.
“The value creation gap between early adopters and followers could widen further in a scenario with faster adoption as data and organizational intelligence accumulate,” it added.
“AI accelerates what happens inside a digitally mature organization; it does not necessarily accelerate the process of becoming one,” it continued.
In a statement sent to Rigzone back in September 2024, Morningstar DBRS said AI adoption by oil and gas companies had been slower compared with other sectors but added that, “as regulations and user cases evolve, AI adoption should pick up”.
“AI can add value for energy companies by increasing efficiencies, optimizing operations, enhancing safety, and reducing emissions,” Morningstar noted in that statement.
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