With the emergence of AI into the mainstream, technology is no longer just an enabler in the background—it's becoming a source of dynamic agency for all of us. It’s impacting decision making, creativity, and value creation, redefining not only how individuals and enterprises interact with information and each other, but also how we innovate and compete.
We’re on the cusp of a digital disruption in energy worthy of such a label.
The last 20 years have seen digital technologies upend the business landscape and revamp cultures and societies worldwide. But across many industries (energy included), change has always been incremental, not transformational.
While each new dazzling innovation (e.g., the cloud, open source, big data, the Internet of Things, software-as-a-service) promised the moon, even integrating them all has led to only modest efficiency gains. We’ve been tuning the engine, so to speak—fiddling with fuel injection, a bigger exhaust, lighter rotating parts—when what we needed was a new vehicle. Perhaps one that we don’t even drive ourselves.
Few energy companies have successfully delivered digital transformation across the value chain at a meaningful scale and with material and lasting performance improvement. Data and knowledge in our industry continues to move slowly by way of manual handoffs across disciplines, leading to sequential decision making, frequent context loss, and significant value leakage.
But things are about to change—and change drastically.
Agentic AI for the energy industry
Our industry faces both cyclical and structural challenges. The pressure to deliver lower-carbon barrels at a lower cost, from aging and increasingly complex assets and infrastructure, while the global talent pool continues to shrink, sees us grappling with a classic “nexus of forces.” Which means the need for a step change that brings about exponential impact has never been greater.
Tech is no longer a passive and reactive tool but a dynamic, proactive teammate. From using machine learning or domain-informed models to support our individual tasks, to stringing tasks together and interacting with their environment, AI agents are becoming the decision-making, action-taking partners we never knew we needed.
From assistants to autonomous agents
We’re quickly headed towards full workflow-scale agents that either have humans in the loop or leave humans freed up to do what humans do best: problem solve and collaborate. This is the world of autonomous agents. They're not just assistants; they’re proactive, goal-oriented systems that can reason, act, and cooperate.
For most of human history, intelligence was a rare commodity. But with the rise of AI, it's no longer scarce. It’s abundant and accessible to every professional, in every discipline, across every organization.
Meanwhile, as AI becomes a force multiplier in technical domains, engineers and geoscientists are being elevated to the role of “systems thinkers.” They’re becoming curators of judgment and decisions, ensuring AI outputs are reliable and contextually correct. This means much of the heavy lifting can be left to AI, freeing people up to frame questions in context and work together.
In other words, their span of control grows. More prospects, more assets, more wells.
The dynamic oil field
Systems thinking becomes immensely practical when operating at scale. It’s a competency shift that allows us to see and govern the oil field as a living, dynamic system, not just a chain of isolated technical puzzles.
Closed-loop processes, new levels of autonomy—these all become possible, giving us a more holistic view across the value chain. Not to mention that better and faster decisions then give rise to significant performance gains; think reduced lifting costs, greater recovery, and lower-carbon processes.
This really is a paradigm shift. Our industry is heading towards a new frontier, and on the other side of it is a world in which digital tech finally realizes what it always promised.
