Artificial intelligence is becoming a defining force to connect people, data, and decision-making throughout the energy sector. It helps us turn our climate ambitions into tangible action.
At the start of 2026, leaders gathered at the World Economic Forum’s Annual Meeting in Davos and described AI as a “strategic enabler” of clean, efficient energy. This is something we are already seeing play out in our own real-world projects, with measurable outcomes that directly support our goal of hitting net zero by 2050.
A case in point is our AI pilot scheme in Norway, where we have been supporting Stanford University through sponsorship and the tech start-up TerraAI to improve the decision-making, efficiency and safety of our Carbon Capture and Storage (CCS) investments.
When uncertainty is a fact of life
The energy industry has always grappled with the challenges of the subsurface world. These challenges range from traditional wells and mines to low-emission approaches such as geothermal energy and CCS, which rely on complex mapping and planning.
Torsten Clemens
On subsurface projects, engineers and geoscientists make high-impact decisions based on incomplete information, often years before a project becomes operational.
Clemens continues:
“As OMV moves from traditional oil and gas operations into geothermal energy and CO2 storage, uncertainty persists. If anything, it increases. These are long-term projects, sometimes taking ten years from conception to execution, and the decisions you make early define safety, performance, and value for decades.”
Scaling low-carbon solutions at a fast enough pace to match the transition requires new technologies combined with smarter ways of working.
That is where AI comes in.
1,000 times faster
The technology that OMV’s pilot is testing in Norway is not generative AI, but analytical, agent-based AI. It’s purpose-built to support decision-making in complex technical environments.
“This is not the kind of AI that writes text or creates images. It’s analytical AI; decision algorithms that crunch real data and uncertainty to guide us to the next best move,” Clemens says.
Developed through OMV’s long-standing sponsorship of Stanford University and brought to life by TerraAI, the system uses advanced decision theory and geostatistics to explore millions of possible field development scenarios. It analyzes seismic data, geological models, and well information to recommend optimal strategies for drilling, CO2 injection, and monitoring.
“I sometimes compare it to chess,” Clemens explains. “In chess, you see the board. Underground, you don’t. The AI has to imagine all possible scenarios, test different moves, and learn step by step which decisions reduce risk and create value.”
By using simulations that run up to 1,000 times faster than conventional tools, the system compresses weeks or months of analysis into hours. That enables teams to move faster without compromising quality or safety.
“Decisions that used to take weeks or months we can now make in hours. That doesn’t mean cutting corners; it means exploring many more options before we choose,” Clemens continues.
Creating value while reducing risk
The approach is already showing tangible benefits. Early internal results from the Norwegian project indicate:
- More than 25% increase in project value
- Around 50% reduction in quantified subsurface risks
- Significant acceleration of development timelines
This has major implications for CCS projects in particular, where safety and regulatory confidence are paramount.
“The system allows us to integrate risk directly into the design phase,” says Clemens. “Injection rates, well paths, and monitoring strategies - all of these are optimized with safety limits in mind.”
This is an ideal application of AI, running simulations and calculations at an unparalleled level of speed and complexity to enhance human decision-making.
A discussion partner, not a decision maker
As discussed in depth across Davos, AI technology must empower people, not sideline them. In this project, engineers and geoscientists remain firmly in control.
“At first, some colleagues were skeptical,” Clemens says. “But very quickly, they saw that the AI became a discussion partner, not a decision-maker. The important thing is transparency. Our engineers can see why the AI suggests something, challenge it, and learn from it. That builds trust instead of a black box.”
The system proposes scenarios and explains trade-offs. Experts challenge assumptions, adjust parameters, and validate results through OMV’s established technical assurance and governance processes.
The AI agent will show its workings, which means the decisions can be critiqued before any real-world action is taken.
This human-AI collaboration allows specialists to spend less time searching for data and more time applying their expertise where it creates the most value.
Collaboration to accelerate the transition
The energy transition cannot be achieved in isolation.
OMV is getting ahead of the call for partnerships to accelerate the use of AI in net-zero technologies. We’re investing around USD 4.5 million over six years in AI research at Stanford University, allowing leading experts to dive into subsurface modelling, decision theory, and safe AI. TerraAI is a start-up emerging from this research ecosystem that translates academic insights into industrial-grade tools.
“Combining academic depth, start-up agility, and industrial experience allows us to move faster,” Clemens says. “That speed matters if we want to scale low-carbon solutions.”
While the pilot is currently focused on CCS in Norway, the potential applications extend across OMV’s low-carbon portfolio, from geothermal energy to other subsurface-dependent projects.
“If we can make decisions faster and safer, we can simply do more projects,” Clemens explains. “That’s essential for reaching our climate targets.”
The AI agents learn from multiple projects over time, enabling a portfolio-level view which helps to balance risks and returns across assets and unlock value at scale.
Clemens notes that as the technology builds, “you start to think less in terms of single assets and more in terms of portfolio trade offs. Which project gives the best risk-return profile for our net-zero path.”
AI as a catalyst for transformation
AI will not replace engineering expertise, nor will it entirely eliminate uncertainty underground. But used responsibly, it can transform how decisions are made.
At OMV, this is what intelligent energy looks like in practice. It’s people empowered by AI, collaborating across disciplines, and accelerating the deployment of low-carbon solutions.
As Clemens puts it: “AI helps us navigate uncertainty with more confidence. And in the energy transition, confidence backed by data and expertise is what allows us to move faster, smarter, and safer.”