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 intensified its AI adoption from the 1980s, with recent efforts focusing on data integration, predictive maintenance, and operational automation leading to significant cost savings (targeting $15 billion by 2027) and productivity increases such as 5% uplift in Bakken gas production.
Chevron has progressively expanded AI integration across exploration, production, and power generation from 2022 through 2025, leveraging partnerships (e.g., with Eliis, Honeywell), proprietary platforms like APOLO and ApEX, and generative AI to enhance operational efficiency, safety, and profitability.
ConocoPhillips has progressively integrated AI and machine learning technologies since 2021, deploying cloud-based cognitive E&P platforms like Schlumberger's DELFI and adopting digital twins globally to optimize oilfield operations and reservoir management.
Phillips 66 has progressively integrated AI across multiple operations from 2023 through 2025, with use cases evolving from design acceleration and cybersecurity to advanced customer-facing checkout systems and midstream asset management.
Marathon Petroleum has progressively integrated AI and digital technologies since 2019, focusing on refinery optimization, maintenance digitization, and acquisition analytics to improve operations and safety, with recent efforts emphasizing scalable AI applications across their asset lifecycle.
Valero Energy has progressively integrated AI technologies from 2023 through 2025, focusing primarily on optimizing energy consumption, enhancing operational efficiencies, and improving sustainability initiatives such as renewable diesel production and energy management.
Kinder Morgan has increasingly positioned itself to benefit from the rising demand for natural gas driven by the growth of artificial intelligence (AI) data centers, with management projecting an additional 7-16 Bcf/d gas demand by 2030.
NextEra Energy has rapidly expanded its AI-driven renewable energy operations and power supply to meet explosive demand linked to AI data centers, with CEO Jeffrey Ketchum leading major collaborations including with Google to revive nuclear plants and invest in natural gas projects since 2024.
Dominion Energy is experiencing rapidly increasing electricity demand driven primarily by AI data centers, prompting a $50B infrastructure investment plan through 2025–2026, focusing on nuclear power (notably Small Modular Reactors at Surry plant) and grid modernization to ensure reliability.
Southern Company has progressively integrated AI from 2019 through 2025, evolving from grid resiliency partnerships (mPrest in 2019) to advanced AI-driven infrastructure and operational management including digital twins (Aetos in 2025) and generative AI for customer engagement.
53 Use Cases in Energy
| Company | Use Case |
|---|---|
| Southern Company | Smart Charging Southern Company pilots automated smart EV charging systems that schedule loads to optimize grid usage and accommodate rising AI-driven power demands from data centers. traditional |
| Chevron | Exploration Data Access Chevron's ApEX generative AI platform increases accessibility to exploration data, enabling faster, smarter decision-making in oil and gas prospecting and reducing manual data processing. generative |
| ExxonMobil | Digital Twin Modeling ExxonMobil and partners use AI-driven digital twins to simulate and optimize equipment performance and drilling operations, improving ROI and monitoring in real time. traditional |
| Southern Company | Nuclear Optimization Southern Nuclear employs AI-driven predictive analytics to minimize unplanned downtimes and optimize fuel usage, significantly improving operational safety and cost efficiency in nuclear power generation. traditional |
| Dominion Energy | Energy Infrastructure Dominion is investing in energy infrastructure such as Small Modular Reactors and offshore wind projects to sustainably meet the growing power demand from AI data centers, supporting tech company partners and enabling growth in the AI sector. traditional |
| Chevron | Drilling Optimization Chevron leverages AI to analyze geological and operational drilling data to reduce drilling costs by 25-50%, increase drilling speed by 30%, and double production per rig, significantly improving operational efficiency and profitability. agentic |
| ExxonMobil | Autonomous Operations ExxonMobil employs autonomous AI agents to reduce operational costs and emissions, supporting the energy transition with advanced intelligent systems optimizing workflow and decision-making. agentic |
| Dominion Energy | Demand Forecasting Dominion Energy uses AI-driven analytics and machine learning algorithms to accurately predict electricity demand spikes, especially due to the rapidly increasing consumption by AI data centers, enabling better grid management and resource allocation. traditional |
| Marathon Petroleum | Predictive Maintenance Marathon Petroleum employs AI to predict equipment failures through data analysis and machine learning models, enabling proactive maintenance and minimizing unplanned downtime across pipelines, terminals, and logistics. agentic |
| Dominion Energy | Grid Resilience Through AI-enhanced analytics and machine learning, Dominion optimizes grid resilience and reliability by dynamically managing fluctuations in power loads caused by AI-driven data center energy consumption growth. traditional |