Chevron Leverages AI to Power Data Centers
Artificial intelligence (AI) is transforming industries and daily life, boosting productivity, improving decision-making, and automating large-scale operations. However, the proliferation of AI also introduces a significant challenge: the substantial power requirements of AI data centers.
Fortunately, AI itself can play a critical role in delivering the reliable energy necessary to meet this growing demand. Chevron is at the forefront of this effort.
The Rising Need for Power
From managing schedules with digital assistants like Siri or Alexa to using tools like ChatGPT, AI has become a ubiquitous part of modern life. This trend extends to the energy industry, where AI helps companies like Chevron analyze data, remotely control equipment, and model hydrocarbon reservoirs. As companies worldwide increasingly integrate AI into their operations, the need for reliable energy to power the AI data centers that support these innovations is soaring.
The International Energy Agency estimates that data centers and data transmission currently account for 1% to 1.5% of global electricity use. This figure is projected to double by 2026. This dramatic increase means that AI data centers will require roughly the same amount of power as the entire country of Sweden.
Reliable Energy Sources for AI
Ensuring a dependable power supply is essential to realize the benefits of AI. Chevron is addressing this challenge by partnering with GE Vernova and Engine No. 1 to develop onsite power plants at select data centers that can run on natural gas.
Jeff Gustavson, President of Chevron New Energies, highlighted the significance of this initiative:
“This is power at a scale that we haven’t seen. AI companies are going faster and faster to deploy this. They’re building bigger and bigger data centers. Meeting those needs fits our capabilities very well, and I couldn’t be more excited or more proud to be working on this.”
AI at Work in the Energy Industry
While Chevron works to power AI data centers, the company is also using AI to improve its internal operations. For decades, Chevron has used data science and analytics to develop energy solutions, establishing a foundation for AI to evolve in this area. Some current applications include:
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AI Underground: AI provides a more accurate picture of subsurface conditions than conventional methods, which is essential for determining the best areas for oil and gas recovery and CO2 storage.
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Reliability: AI supports predictive maintenance by analyzing real-time sensor data and detecting anomalies, such as leaks, to keep assets operational. For example, Chevron is using AI-equipped drones to inspect facilities and monitor for issues.
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Transportation: AI optimizes routes and cargo loads, allowing Chevron to improve transportation efficiency and safety across land, sea, and air.
Chevron’s dual approach of powering and utilizing AI underscores its commitment to innovation and reliable energy solutions for the future.
