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 steadily increased its integration of AI across operations since the 1980s, with notable acceleration in AI-driven predictive maintenance, data unification, and use of machine learning to boost production efficiency as seen by a 5%+ production increase in Bakken gas lift wells by 2024.
Chevron has progressively integrated AI and machine learning across its operations from 2022 through early 2026, focusing on optimizing oil and gas exploration, drilling efficiency, operational safety, and power supply for AI data centers. Key innovations include AI-driven platforms like ApEX and APOLO, partnerships with firms like Eliis and Honeywell, and significant investments in natural gas power plants for data centers.
ConocoPhillips has progressively increased its adoption of AI and machine learning technologies from 2021 through early 2026, applying advanced analytics, digital twins, and automated workflows across exploration, drilling, and operational optimization to improve efficiency, decision-making, and cost management.
Phillips 66 has steadily increased AI adoption since 2018, leveraging advanced analytics and AI-powered tools for operational efficiency, cybersecurity, and customer experience enhancements, exemplified by their 2025 launch of an AI-accelerated checkout system with Mach 1.
Marathon Petroleum has increasingly integrated AI and machine learning technologies since 2019, focusing on digital monitoring, operational optimization, and predictive maintenance to enhance refinery efficiency, safety, and cost management.
From mid-2023 to early 2026, Valero Energy has progressively adopted AI technologies focusing on optimizing energy consumption, operational efficiency, and refining margins management, while expanding into sustainable fuels including renewable diesel and sustainable aviation fuel.
Kinder Morgan has experienced increasing natural gas demand driven significantly by the growth of AI applications and data centers since early 2024, positioning the company as a key energy supplier to power AI infrastructure.
NextEra Energy has significantly expanded its AI adoption from early exploratory phases in 2018 to fully integrated AI-driven operations by 2025, leveraging machine learning for renewable asset optimization, grid management, and predictive maintenance, resulting in substantial cost savings and operational efficiency gains.
Dominion Energy has experienced rapidly increasing electricity demand driven by the surge in AI and data center growth, particularly in Northern Virginia, leading to a multibillion-dollar infrastructure investment plan exceeding $50 billion focused on nuclear, renewable, and grid modernization projects.
Southern Company has progressively integrated AI technologies starting from grid resilience enhancement in 2019 to advanced AI-driven operational and customer engagement solutions by 2026, showing a clear increasing adoption trend.
52 Use Cases in Energy
| Company | Use Case |
|---|---|
| Valero Energy | Sustainability Transition AI supports the development and optimization of cleaner fuel technologies like renewable diesel and sustainable aviation fuel, guiding Valero's strategic green energy initiatives. traditional |
| Southern Company | AMI Analytics Integration of AI and traditional analytics in Advanced Metering Infrastructure (AMI) to create an intelligence hub, enhancing smart meter data utilization for operational insights and customer service. traditional |
| Kinder Morgan | Infrastructure Expansion Leveraging AI-driven insights on energy consumption trends, Kinder Morgan strategically invests in and expands its natural gas pipeline infrastructure to meet the surging demands of AI and data center growth. agentic |
| Phillips 66 | Predictive Maintenance Phillips 66 uses AI-powered analytics via platforms like Seeq to detect anomalies such as coke drum blowouts, enabling proactive maintenance to reduce downtime and operational risks. traditional |
| ExxonMobil | Operational Intelligence AI is used to turn disparate data from sensors, imagery, and other sources into actionable intelligence that advances energy security and lowers emissions in ExxonMobil's operations. traditional |
| NextEra Energy | AI Energy Supply NextEra is expanding energy generation—through renewables, nuclear, and natural gas—specifically to meet surging electricity demand from AI data centers, partnering with major tech firms like Google to deliver clean and reliable power. agentic |
| Chevron | Exploration Efficiency AI platforms like ApEX and APOLO analyze exploration data and geological information to identify optimal drilling locations faster and more accurately, reducing exploration costs by up to 80%. generative |
| ExxonMobil | Resource Modeling AI and supercomputing are embedded in reservoir modeling and seismic data interpretation at ExxonMobil, enabling improved extraction planning and unlocking more hydrocarbons. traditional |
| Southern Company | Demand Forecasting Southern Nuclear and partners utilize AI models such as ThermalLimits.ai to optimize nuclear power plant operations, improve fuel utilization, and predict potential derates with high accuracy. traditional |
| ConocoPhillips | Decision Automation Using AI and machine learning to automate complex decision-making processes in field development and drilling operations, ConocoPhillips improves speed and quality of operational choices, impacting production outcomes. agentic |