Artificial Intelligence in Energy Companies
We analyzed the enterprise AI use cases of 10 energy companies to understand trends, impact, and insights.
Energy companies' adoption of AI
Overview
ExxonMobil has progressively integrated AI and machine learning technologies across its operations from 2020 through 2025, focusing on predictive maintenance, data unification, and workflow automation to optimize oil and gas production, reduce downtime, and increase operational efficiency.
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.
ConocoPhillips has progressively integrated advanced AI and machine learning technologies from 2021 through 2025, focusing on seismic data processing, reservoir management, and operational optimizations, including portfolio-wide digital twin implementations and AI-driven workflows for decision-making.
Phillips 66 has progressively adopted AI technologies since 2018, leveraging AI to enhance operational design processes, cybersecurity, data protection, and digital transformation efforts, showing an increasing and strategic integration of AI up to 2025.
Marathon Petroleum has progressively integrated AI and machine learning technologies since 2019, advancing from digital monitoring and optimization partnerships to AI-driven refinery optimization and intelligent alert systems managing over 4,000 wells by 2023.
Valero Energy has progressively integrated AI to optimize energy consumption and efficiency across its operations, with notable initiatives increasing energy savings by up to 20% as of Q1 2025.
Since early 2024, Kinder Morgan has experienced increasing positive market sentiment driven by the rising energy demand linked to AI and data center growth, with Chairman Richard Kinder highlighting 'tremendous' AI-driven natural gas demand and the company securing major natural gas projects like South System Expansion 4 and Mississippi Crossing.
NextEra Energy has deeply integrated AI into its operations and growth strategy by 2025, with AI-driven optimization contributing to a 25-30% reduction in maintenance costs and 70-75% fewer equipment failures, underpinning sustained revenue growth and a 12% CAGR since 2020.
Dominion Energy is experiencing rapid growth in electricity demand driven by AI data centers, particularly in Northern Virginia, leading to a $50 billion infrastructure investment to support this expansion while balancing renewable energy integration.
Southern Company has progressively integrated advanced AI technologies from 2019 through 2025, starting with partnerships to enhance grid resiliency and evolving to AI-driven operational intelligence and customer engagement, including digital twin infrastructure management via Aetos.
46 Use Cases in Energy
| Company | Use Case |
|---|---|
| ExxonMobil | Autonomous Operations The company uses autonomous AI agents to optimize operations, reduce emissions, and cut costs, advancing its position in the energy transition and operational sustainability. agentic |
| Dominion Energy | Load Prediction Dominion Energy leverages AI algorithms to predict electricity loads driven by data center growth and AI demand, enabling more accurate capacity planning and grid reliability management. traditional |
| NextEra Energy | Automated Trading NextEra uses AI-driven automatic trader modules that analyze market data to autonomously generate optimal bids for energy market transactions, improving trading outcomes and client savings. agentic |
| NextEra Energy | Predictive Maintenance NextEra uses machine learning algorithms to analyze sensor and operational data from renewable assets and nuclear equipment to predict equipment failures and schedule maintenance proactively, reducing downtime and lowering maintenance costs by up to 30%. traditional |
| Kinder Morgan | Demand Forecasting The company utilizes machine learning models to forecast natural gas demand driven by AI data center growth and new technology trends to optimize pipeline capacity planning and investment decisions. traditional |
| ConocoPhillips | Information Extraction Large language models autonomously extract and synthesize vital information from vast datasets to inform field development decisions, thereby enabling faster and better-informed strategic planning. agentic |
| Marathon Petroleum | Risk Mitigation Using AI systems, Marathon Petroleum enhances process safety by identifying potential hazards and cyber vulnerabilities to mitigate operational risks proactively. agentic |
| Southern Company | Infrastructure Management Using digital twin technology via Aetos, Southern Company digitizes its assets to enable virtual inspections, remote assessments, and faster decision making, enhancing safety and reducing physical site visits. traditional |
| Valero Energy | Renewable Strategy Valero leverages AI insights and partnerships to drive its renewable fuel initiatives including Diamond Green Diesel and battery storage projects, aimed at energy transition and sustainability. traditional |
| Southern Company | Customer Engagement Southern Company leverages generative AI and machine learning to transform customer interactions, personalizing services and improving satisfaction through advanced analytics and conversational AI. generative |