Rudy Lai

AI @ Chevron

Major U.S. integrated energy firm
Industry
Last updated
July 3, 2025 at 10:44 AM

Summary

  • Chevron has progressively integrated AI technologies from Q4 2022 through 2025, focusing on operational excellence, safety, seismic interpretation, and energy reliability, reflecting increasing adoption and AI-driven innovation.
  • Significant collaborations include partnerships with Eliis for seismic AI, Honeywell for refinery AI-assisted solutions, and GE Vernova and Engine No.1 for natural gas power plants to support AI data centers, emphasizing strategic expansion in AI-powered energy and efficiency solutions.
  • Chevron leverages AI to boost oil extraction efficiency in the Permian Basin, improve worker safety with digital twins and AI-driven automation, and provide reliable energy for AI data centers, contributing to cost reduction, environmental stewardship, and enhanced operational safety.

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5 AI Use Cases at Chevron

Energy Reliability
2025
Traditional
Generative
Agentic
Outcome
Costs
Chevron leverages AI to optimize the supply and management of natural gas power plants, directly supporting energy-intensive AI data centers, thereby ensuring reliable energy delivery crucial for AI operations. [1][2][3]
Operational Efficiency
2024
Traditional
Generative
Agentic
Outcome
Revenue
Chevron uses AI to analyze large datasets and generate predictions to optimize oil extraction and production processes, significantly boosting productivity and revealing best opportunities as in the Permian Basin. [1][2]
Process Optimization
2024
Traditional
Generative
Agentic
Outcome
Costs
The collaboration with Honeywell focuses on developing AI-assisted solutions to optimize refining processes, aiming to improve efficiency, reduce cycle times, and enhance profitability. [1]
Seismic Interpretation
2024
Traditional
Generative
Agentic
Outcome
Risk
Chevron collaborates with Eliis to integrate advanced algorithms for seismic data interpretation, enhancing exploration and reducing uncertainty through AI-driven geoscientific workflows. [1][2]
Safety Automation
2023
Traditional
Generative
Agentic
Outcome
Risk
Using digital twins, simulations, and AI-driven tools, Chevron enhances worker safety by automating hazardous processes and alerting to operational anomalies, as demonstrated in collaborations with Percepto drones for autonomous inspections. [1][2]

Timeline

2025 Q3

1 updates

A Klover report analyzes Chevron's AI strategy and projected dominance in the energy sector powered by AI capabilities.

2025 Q2: no updates

2025 Q1

6 updates

Chevron invests in natural gas plants to power AI data centers, partnering with Engine No.1 and GE Vernova, highlighting AI's electricity demand; uses AI-powered drones with Percepto for automated inspections.

2024 Q4

2 updates

Strategic collaboration with Honeywell to develop AI-assisted refining process solutions; AI enhances oil extraction productivity and reduces cycle times in the Permian Basin.

2024 Q3

4 updates

Supreme Court overturns Chevron deference, complicating AI regulation while Chevron advances use of generative AI, digital twins, and robotics for data analysis, predictions, and workforce protection.

2024 Q2

2 updates

Chevron collaborates with Eliis to develop advanced AI algorithms for seismic data; a legal decision involving Chevron impacts AI regulations and privacy rules in the US.

2024 Q1

1 updates

Partnership with Eliis to revolutionize AI in seismic interpretation, aiming to integrate AI technology into geoscientific workflows.

2023 Q4

1 updates

AI used to enhance operational safety with digital twins under leadership of Ellen Nielsen; AI reduces dangerous manual labor and improves efficiency.

2023 Q3

2 updates

Chevron integrates AI and machine learning across its value chain to enhance efficiency, environmental stewardship, and safety; joins Responsible AI (RAI) Institute to promote responsible AI application.

2023 Q2: no updates

2023 Q1: no updates

2022 Q4

1 updates

Chevron begins AI adoption focusing on business goal alignment with two specific AI use cases.