Rudy Lai

AI @ ExxonMobil

Largest U.S. oil company
Industry
Last updated
July 3, 2025 at 10:44 AM

Summary

  • 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.
  • From 2024 onward, ExxonMobil has pivoted towards leveraging AI-centric strategies not only to optimize internal processes but also to position itself as a leader in powering AI data centers via low carbon natural gas plants with carbon capture technology, targeting substantial cost savings ($15 billion by 2027) and emission reductions.
  • Key leadership like Sarah Karthigan and executives including Andrew Curry have driven AI adoption, emphasizing autonomous AI agents and supercomputing integration, enabling ExxonMobil to sufficiently address energy demands of AI infrastructure while expanding its influence in AI energy domains and digital transformation partnerships.

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7 AI Use Cases at ExxonMobil

Digital Twins
2025
Traditional
Generative
Agentic
Outcome
Revenue
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. [1][2]
Engineering Collaboration
2025
Traditional
Generative
Agentic
Outcome
Costs
Collaboration with CoLab Software expedited AI tools to support engineering design and communication on offshore oil rig projects, enhancing project timelines and safety. [1]
Carbon Emission Reduction
2024
Traditional
Generative
Agentic
Outcome
Risk
ExxonMobil collaborates to power AI data centers with natural gas plants equipped with carbon capture technologies, actively reducing emissions associated with energy generation for AI workloads. [1][2]
Energy Demand Forecasting
2024
Traditional
Generative
Agentic
Outcome
Revenue
AI is used to build technology roadmaps optimizing oil and gas production to meet the rising energy demands of AI infrastructure and global data centers, linking supply with anticipated consumption. [1]
Safety Enhancement
2024
Traditional
Generative
Agentic
Outcome
Risk
By leveraging machine learning and computer vision, ExxonMobil enhances workplace safety protocols to reduce accidents and improve employee well-being. [1]
Production Optimization
2024
Traditional
Generative
Agentic
Outcome
Revenue
Machine learning workflows have been deployed to analyze vast sensor and operational data to boost oil and gas production, including increasing output by over 5% in Bakken gas lift fields. [1][2]
Predictive Maintenance
2023
Traditional
Generative
Agentic
Outcome
Costs
ExxonMobil utilizes AI and machine learning to predict equipment failures and schedule maintenance proactively, which reduces unplanned downtime and lowers labor costs across its operations. [1][2]

Timeline

2026 Q1

1 updates

Continued emphasis on AI-powered integration of diverse data sources like sensors and imagery to advance energy security and lower emissions, focusing on making AI benefits accessible and operationalizing data internally.

2025 Q4

4 updates

Advanced collaborations and contracts including with TechnipFMC for AI-driven digital twins; focused on AI and supercomputing integration for reservoir modeling and seismic interpretation; ongoing talks to power and decarbonize AI data centers with low carbon natural gas with carbon capture technology; multi-company partnerships shaping AI infrastructure and energy demand.

2025 Q3

3 updates

ExxonMobil scaled oil and gas production to meet AI and data center energy needs; employed autonomous AI agents to cut costs, reduce emissions, and drive energy transition; formed partnerships with Google and NextEra for AI infrastructure build-out.

2025 Q2: no updates

2025 Q1

1 updates

Partnership with CoLab Software advanced AI-assisted engineering design collaboration for offshore oil rigs.

2024 Q4

3 updates

Engaged in powering AI data centers via natural gas plants with carbon capture, marking collaboration between oil and tech sectors; targeting $15B operating cost savings by 2027 through AI and process automation.

2024 Q3

1 updates

Implemented AI-driven technology roadmaps to optimize oil and gas production in locations from Guyana to Australia.

2024 Q2

3 updates

Machine learning workflows increased production output by over 5% in Bakken gas lift fields; AI enhanced safety protocols to reduce workplace accidents.

2024 Q1: no updates

2023 Q4: no updates

2023 Q3

2 updates

Established a secure data strategy to identify AI-ready datasets; employed AI in predictive maintenance reducing unplanned downtime and labor costs.

2023 Q2: no updates

2023 Q1

1 updates

ExxonMobil applied AI to integrate siloed data facilitating faster and more efficient oil well development.

2022 Q4: no updates

2022 Q3: no updates

2022 Q2: no updates

2022 Q1: no updates

2021 Q4

1 updates

Leadership spotlight: Sarah Karthigan led AI projects focusing on self-healing IT operations strategies.

2021 Q3: no updates

2021 Q2

1 updates

Partnership with Microsoft Azure enabled using IoT and ML to reduce downtime and boost productivity across operations.

2021 Q1: no updates

2020 Q4

1 updates

Initial AI foundations: ExxonMobil started studying AI and networking equipment since the 1980s, with its AI efforts visible in collaborations such as with Intel focusing on edge computing.