The oil and gas industry is undergoing a significant transformation, with major companies rapidly adopting artificial intelligence and robotics to maximize savings, optimize operations, and boost earnings. This digitalization, though not new to the energy sector, has seen accelerated advancements with AI capabilities. Companies are using robot dogs, AI-enabled drones, and autonomous haul trucks for inspections and surveillance, aiming to minimize costs and maximize profits in an industry traditionally reliant on manual labor.
Several supermajors are at the forefront of this technological shift. ExxonMobil, for instance, is using autonomous drilling in deep water off the coast of Guyana, employing a proprietary AI-driven drilling advisory system for optimal parameters and closed-loop automation. Chevron is leveraging AI in the Permian Basin to extract more oil with less effort, boasting an over 80% improvement in execution performance since 2019. This has led to work hour savings, increased monitoring frequency at remote sites, and faster issue detection.
Canadian energy companies are also embracing automation to combat lower commodity prices. Suncor Energy Inc. has been piloting driverless trucks in the oilsands, potentially saving 10-13% off operating costs with a phased implementation over three to five years, managing job reductions through attrition. Similarly, Precision Drilling Corp. aims to commercialize new automated and robotics systems to lower drilling costs by 8-12% and reduce human error. The global robotics market, valued at $90.2 billion in 2024, is projected to reach $205.5 billion by 2030, with the oil and gas sector being a key contributor to this growth, driven by demand for inspection, monitoring, and maintenance applications.
Robotics plays a crucial role in harsh environments like offshore and subsea operations, where limited access and extreme conditions make human intervention costly and risky. Quadruped robots and hazardous-zone-certified inspection platforms are inspecting pipelines, flare stacks, storage tanks, and offshore platforms. While the adoption of these technologies offers substantial benefits in safety, efficiency, and asset integrity, it also introduces challenges such as the need for significant capital investment, system integration complexities, operational reliability in extreme environments, and increased cyber risks due to heightened digitalization. Despite these challenges, the integration of robotics with digital twins, edge intelligence, and predictive analytics is paving the way for a new era of automated and resilient oil and gas operations.
