Chevron bets $1 billion on Bengaluru GCC, now 1,000 engineers strong

Chevron

Chevron, one of the world’s leading energy companies, has announced the rapid expansion of its Global Capability Centre (GCC) in Bengaluru, with an investment commitment of $1 billion over the next four to six years.

The centre, now home to over 1,000 engineers, marks Chevron’s largest-ever technology investment outside the United States.

Speaking at a media briefing, Akshay Sahni, Country Head of Chevron India, described the facility as a “state-of-the-art technology hub” that shows Chevron’s global operations with advanced engineering, digital solutions, and artificial intelligence.

The GCC’s core mission is to integrate AI, automation, and digital twins into every aspect of Chevron’s energy workflows, helping improve efficiency, reliability, and safety across its global network.

“The facility represents our single largest investment in technology capability and capacity building outside our US headquarters,” Sahni said. “We are building talent and expertise across all STEM disciplines from mechanical and chemical engineering to AI and robotics.”

Spread across three floors and spanning 3 lakh square feet, the Engineering Innovation Excellence Centre is designed to support Chevron’s projects worldwide, from deep-water drilling operations to liquefied natural gas (LNG) facilities and digital monitoring centres.

Sahni added that Chevron’s approach differentiates it from other GCCs by combining domain experts such as engineers, geoscientists, and process specialists with AI and cybersecurity experts in a collaborative environment.

The Bengaluru hub includes cutting-edge facilities such as a Robotics Lab and Digital Twin Lab, allowing engineers to simulate, monitor, and optimise operations remotely. A dedicated AI Accelerator team works alongside domain specialists to accelerate AI-powered solutions for global deployment.

Chevron’s $1 billion investment will primarily go toward expanding talent, upgrading IT infrastructure, and enhancing high-performance computing systems to support data-intensive energy modeling.