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 across its operations since the 1980s, with significant advancements in using machine learning and data analytics to enhance oil and gas production efficiency, predictive maintenance, and safety protocols, leading to increased output and reduced downtime.
Chevron has progressively integrated AI and machine learning throughout its operations since at least 2022, moving from foundational AI exploration to advanced generative AI platforms and autonomous systems by 2025, leading to significant operational improvements and cost reductions.
ConocoPhillips has steadily increased AI adoption from 2021 through early 2026, integrating machine learning and advanced analytics widely across exploration, drilling optimization, reservoir management, and operational decision-making.
Phillips 66 has progressively integrated artificial intelligence across its operations since at least 2018, with strong adoption growing especially between 2023 and 2026, including AI applications in equipment design, midstream asset management, cybersecurity, data protection, and customer checkout experience.
Marathon Petroleum has progressively integrated AI and digital technologies since 2019, partnering with firms like Hypergiant Industries and leveraging AWS for intelligent alerts and refinery optimization, significantly enhancing operational efficiency and safety.
Valero Energy has progressively integrated AI technologies from 2023 through early 2026, mainly focusing on optimizing energy consumption, predictive analytics for refinery operations, and enhancing operational efficiency internally.
Kinder Morgan's natural gas pipeline business has seen significant demand growth driven by the artificial intelligence (AI) and data center boom, with management anticipating up to an 8 Bcf/d incremental gas demand increase by 2030, supported by a $9.3 billion project backlog largely dedicated to natural gas infrastructure expansion.
NextEra Energy has increasingly integrated AI into its operations since at least 2018, growing from initial AI use in nuclear work management and equipment reliability in 2021 to advanced market dispatch, predictive maintenance, and grid balancing by 2025, with AI being a core pillar of competitive advantage.
Dominion Energy is significantly expanding its energy infrastructure, notably nuclear and renewable resources, to meet escalating power demands driven by AI data centers primarily in Virginia, with a planned $50 billion investment through 2025.
Since 2019, Southern Company has progressively integrated AI technologies across grid management, safety, regulatory and financial data handling, and infrastructure operations, culminating in extensive AI-driven capacity expansions by 2025–2026, aligned with surging AI-related energy demand.
48 Use Cases in Energy
| Company | Use Case |
|---|---|
| Southern Company | Load Forecasting Southern Company leverages AI-powered analytics and Databricks platform to transform and analyze data from over 4.6 million smart meters for improved energy usage forecasting and operational decision-making. traditional |
| Phillips 66 | Predictive Maintenance Phillips 66 uses advanced analytics via Seeq software integrated with AI to detect and minimize incidents like coke drum blowouts, enabling proactive maintenance and reducing unplanned downtime. traditional |
| Marathon Petroleum | Energy Provisioning Marathon is leveraging its natural gas assets to supply energy for AI data centers, thereby capitalizing on increased AI-driven energy demand and creating new revenue streams. traditional |
| NextEra Energy | Energy Supply Planning Using AI-powered analytics in partnership with Google Cloud, NextEra plans and operates large-scale clean energy projects geared towards powering energy-intensive AI data centers, including nuclear plant restarts and natural gas expansions. agentic |
| ExxonMobil | Digital Twins Through contracts with technology partners like TechnipFMC, ExxonMobil uses AI-driven digital twins to simulate and optimize oilfield operations and project planning, increasing efficiency and investment returns. agentic |
| Chevron | Exploration Automation With the ApEX generative AI platform, Chevron automates manual tasks in exploration data analysis, increasing access to insights and accelerating decision-making processes to enhance resource discovery and evaluation efficiency. generative |
| Southern Company | Nuclear Optimization Southern Nuclear developed Nuclear-Grade AI software in partnership with Blue Wave AI Labs to provide predictive analytics, enhance operational safety, prevent unplanned derates, and optimize fuel usage with less than 0.75% bias. agentic |
| Dominion Energy | Demand Forecasting Dominion Energy uses machine learning algorithms to predict electricity demand spikes, particularly driven by AI data centers, allowing for more efficient and reliable grid management. traditional |
| ConocoPhillips | Workforce Efficiency AI technologies automate administrative and operational tasks resulting in significant workforce reductions and enhanced operational efficiency, highlighting transformation in staffing models and cost structures. traditional |
| Chevron | Drilling Optimization Chevron uses AI systems including the proprietary APOLO platform and generative AI tools like ApEX to analyze geological and exploration data. These systems optimize drilling locations, increase drilling speed by 30%, reduce costs by up to 50%, and double well production per rig by improving subsurface analysis and resource evaluation. agentic |