Another year, but not “just another” CERAWeek.
With accelerating industry change, this year’s conference in Houston delivered strong perspectives on navigating geopolitical shifts, climate change, AI implications, and other key themes for the Energy sector. While these topics are discussed cyclically, they are all becoming more interconnected than ever - and at a faster pace than expected.
For example, AI's high energy demands are changing the energy landscape, with short-term gaps to be filled with more natural gas-powered capacity. At the same time, AI is already helping to drive key operational changes in daily control, field, and planning workflows that make fossil fuel and byproduct extraction safer, more efficient, and more climate-friendly.
In fact, efficiency—not necessarily more drilling—seems to be where operators will place their bets in 2025. Baker Hughes CEO Lorenzo Simonelli is confident that US oil and gas producers are unlikely to increase spending this year, with output increases primarily coming from improved operating efficiencies (Reuters, March 10, 2025). So how can operators fast-track these efficiencies with technology?
Data & AI offers a clear path to improving operations
In addition to leveraging newer, more advanced rigs and equipment, operators have a massive opportunity to adopt data and AI-driven practices that improve productivity without investing in large capital projects. This was its own theme at CERAWeek, with key discussions around lessons learned, best practices, and clarifying what’s “real” over what’s still “hype.” Here were our takeaways:
1. No silver bullet yet to adoption—but AI-enhanced digital tools offer best path
As with any significant change management project, AI success in energy operations is being judged by how daily workflows change as a result of the new technology and process. Today, progress is being made, and digital tools and AI copilots come together to answer questions in seconds, which used to take hours from field technicians on handheld devices to remote control centers with banks of monitors. Operators get more efficient when collaboration on complex real-world business questions like troubleshooting, maintenance work, and turnaround planning becomes seamless.
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2. AI needs to move to the field—scaling will be what drives material OPEX change
AI proofs of concept—whether Gen AI or machine learning-based—are a dime a dozen these days, with straightforward value in a “laboratory environment.” But it’s easier to demonstrate quick wins here than proving value and adoption at scale. Forward-thinking CDOs and COOs have now set their sights on what it takes to replicate AI success across unique fields or distinct refining operations without adding linear human or technology costs. Here, AI is already being used to help scale AI capable of abstracting non-standard site operations, data stores, and equipment into standard operating models for near “cut and paste” deployment at the next site in months, not years.
See how one organization scaled data & AI solutions to 50 sites in just two years
3. AI Success is a function of an adaptable data layer—no need to be perfect all at once
Energy operations aren’t static, and neither is your data. It’s no secret that more focus has to be put into data management, access, and quality so that AI and other digital capabilities can be trusted in critical environments. While data stacks remain complex, with many vendors competing to control ERP, process, and other data, success accelerates when digital teams embrace open, scalable data platforms that return control to operations teams. Data platforms need to meet operations teams where they are and be able to grow and adapt as operational needs and scaling plans evolve.
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Tangible next steps
As always, CERAWeek offered fresh industry perspectives on the key challenges and opportunities that must be addressed in the near and distant future. Addressing rapid industry change gets easier with data-driven approaches and AI. So what should operators do next to improve productivity and efficiency?
- Get up to speed on how Generative AI offers unprecedented opportunities for industrial operators by reading this definitive guide.
- See how organizations across the value chain already deliver better operational outcomes by working with Cognite.
- Identify what’s blocking your progress and discover our prescriptive approach to quickly implementing and scaling AI use cases in less than a quarter.