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 demonstrated a progressive and expanding adoption of AI technologies from the 1980s through 2025, increasingly leveraging AI for operational efficiencies, well development, predictive maintenance, and strategic energy management, including powering AI data centers.
Chevron has progressively integrated AI technologies across its operations since 2022, focusing on operational efficiency, safety, exploration, and energy supply for AI data centers, with significant partnerships including Eliis and Honeywell.
ConocoPhillips has progressively integrated advanced AI and machine learning technologies into its exploration, drilling, and operational optimization processes since 2021, achieving cost reductions and efficiency gains notably in the Permian Basin and Lower 48 operations.
Phillips 66 has progressively integrated AI technologies since at least 2018, focusing on applications that enhance operational efficiency, data protection, and customer experience, as indicated by initiatives like AI-assisted equipment design and automated checkout solutions.
Marathon Petroleum has steadily integrated AI and digital technologies from 2019 through 2025, evolving from digital monitoring and machine learning partnerships to advanced AI-driven refinery optimization and enterprise-wide digital transformation initiatives.
Valero Energy has progressively integrated AI technologies from 2023 through 2025, focusing on optimizing energy consumption, enhancing operational efficiency, and exploring renewable fuels and battery initiatives, reflecting a trend of increasing AI adoption especially in energy management and refining processes.
Kinder Morgan's involvement with AI has primarily been as an energy infrastructure enabler, with AI-driven demand from data centers significantly increasing natural gas consumption and pipeline utilization from 2024 onwards.
NextEra Energy has significantly integrated AI and machine learning into operational areas including renewables dispatch, grid load balancing, equipment reliability, and predictive maintenance, realizing 25-30% maintenance cost reductions and cutting equipment failures by up to 75%.
Dominion Energy has experienced a significant increase in power demand driven by the rapidly growing AI data center industry, particularly in Northern Virginia. This surge has led the company to accelerate a $50 billion infrastructure investment plan focused on supporting AI-related energy consumption while balancing renewable and nuclear power development.
Southern Company has progressively expanded AI adoption from pilot collaborations (e.g., with mPrest in 2019 and HData in 2023) to comprehensive integration across operations by 2025, including grid resiliency, worker safety, regulatory data management, and infrastructure management.
50 Use Cases in Energy
| Company | Use Case |
|---|---|
| ExxonMobil | Digital Twins ExxonMobil collaborates with partners like TechnipFMC, using AI to create digital twins of assets, enabling real-time simulation and optimization, leading to operational efficiencies and partner market value gains. traditional |
| ExxonMobil | Autonomous Agents ExxonMobil employs autonomous AI agents to plan and execute activities that reduce operational costs and emissions, and to maintain competitive advantage in the energy transition. agentic |
| NextEra Energy | Load Forecasting Using AI models trained on vast datasets including weather, historical performance, and demand patterns, NextEra Energy achieves highly accurate grid load and power demand forecasting (95% accuracy), optimizing energy dispatch and market bidding strategies. traditional |
| NextEra Energy | Predictive Maintenance NextEra Energy applies machine learning algorithms to monitor equipment condition in wind, solar, and nuclear assets to predict potential failures, enabling proactive repairs that significantly reduce downtime and maintenance costs by 25-30%. traditional |
| Chevron | Operational Efficiency Chevron leverages AI systems to optimize drilling operations, resulting in reduced drilling costs by up to 50%, increased drilling speed by 30%, and significantly higher well production per rig. agentic |
| Valero Energy | Renewable Integration Valero explores AI to support renewable fuels and battery storage initiatives, aiming to advance energy transition efforts and enhance sustainability in its product portfolio. traditional |
| Southern Company | Infrastructure Automation Implementation of Aetos digital twin technology enables virtual inspections and remote assessments at multiple facilities, accelerating decision-making and enhancing safety while reducing onsite inspection needs. agentic |
| Valero Energy | Energy Trading Valero utilizes AI-driven predictive analytics and market data to optimize its trading strategies, enhancing investment decisions and adapting to market fluctuations effectively. traditional |
| Dominion Energy | Grid Management The company employs machine learning models to optimize grid reliability and resilience, managing the challenge of volatile AI data center loads while integrating renewable and nuclear power sources. traditional |
| Dominion Energy | Operational Automation Dominion integrates AI software like Nuclearn’s CAP AI at the Surry nuclear plant to automate nuclear plant operations, improving efficiency, reducing manual workload, and ensuring system reliability. agentic |