Rudy Lai

AI @ ExxonMobil

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

Summary

  • ExxonMobil has steadily expanded its AI integration from initial exploratory and IT self-healing projects in the 1980s and early 2020s towards comprehensive operational applications including predictive maintenance, production optimization, and autonomous AI agents by 2025.
  • Recent efforts focus heavily on powering the AI revolution externally by supplying natural gas and carbon-captured energy to data centers, signaling a strategic shift to serve Big Tech's AI infrastructure needs alongside internal AI-driven efficiency gains and cost savings, targeting $15 billion operating cost reductions by 2027.
  • Key figures such as Sarah Karthigan and Andrew Curry lead AI adoption, with collaborations including Microsoft Azure and CoLab Software, highlighting ExxonMobil's systemic data unification, advanced machine learning workflows boosting production by over 5%, and pioneering AI-based technology roadmaps for global oil and gas optimization.

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6 AI Use Cases at ExxonMobil

Energy Supply
2025
Customer Facing
Traditional
Generative
Agentic
Outcome
Revenue
Building natural gas plants equipped with carbon capture technologies to provide reliable, low-carbon power to AI data centers globally, supporting the AI revolution's energy needs. [1][2]
Operational Autonomy
2025
Traditional
Generative
Agentic
Outcome
Costs
Deployment of autonomous AI agents across the energy value chain to optimize costs, emissions, and support the energy transition, advancing AI-driven autonomous operations. [1]
Engineering Collaboration
2025
Traditional
Generative
Agentic
Outcome
Costs
Utilizing AI tools for engineering design collaboration and communications on offshore oil rigs to expedite development and improve team efficiency. [1]
Production Optimization
2024
Traditional
Generative
Agentic
Outcome
Revenue
Automated machine learning workflows forecast production parameters to optimize gas lift output, achieving over 5% production increase in key fields such as Bakken. [1]
Predictive Maintenance
2023
Traditional
Generative
Agentic
Outcome
Costs
ExxonMobil uses AI to analyze equipment and operational data to predict and prevent unplanned downtime, reducing labor costs and operational disruptions. [1][2]
Data Unification
2023
Traditional
Generative
Agentic
Outcome
Costs
Integrating disparate data silos and securing data strategies to ensure readiness for advanced AI and ML capabilities, enabling more efficient operations and analytics. [1]

Timeline

2026 Q2: no updates

2026 Q1

1 updates

Focused on integrating multiple data sources (sensors, images) via AI to advance energy security and lower emissions, emphasizing the role of people in making AI-powered transformations happen.

2025 Q4

9 updates

Advanced discussions and contracts to power AI data centers with natural gas and carbon capture; partnered with TechnipFMC for AI-enabled digital twins boosting technology buy points; collaborations with Google and NextEra to build AI infrastructure; leveraged AI to turn predictive maintenance and energy optimization into business intelligence.

2025 Q3

4 updates

Adopted autonomous AI agents across the energy production value chain to cut costs, reduce emissions, and expand energy transition leadership; strategic shift toward serving global AI infrastructure energy needs documented.

2025 Q2: no updates

2025 Q1

1 updates

Partnered with CoLab Software to deploy AI tools for engineering design collaboration and communication on offshore oil rigs, enhancing operational efficiency.

2024 Q4

5 updates

Expanded AI applications to analyze customer data for personalized services; initiated construction of natural gas plants with carbon capture to power AI data centers; targeted $15 billion operating cost savings by 2027 via AI and process automation.

2024 Q3

1 updates

Built technology roadmaps using AI to optimize oil and gas production worldwide, from Guyana to Australia.

2024 Q2

3 updates

Implemented automated ML workflows increasing Bakken gas lift production by more than 5%; enhanced safety protocols reducing workplace accidents; leadership comments issued regarding AI impact on future oil and gas operations.

2024 Q1: no updates

2023 Q4: no updates

2023 Q3

2 updates

Company focused on unified data strategy to identify data readiness for AI and ML capabilities; implemented predictive maintenance reducing unplanned downtime and labor costs.

2023 Q2: no updates

2023 Q1

1 updates

ExxonMobil accelerated well development by integrating disparate data silos using AI, enabling 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

Sarah Karthigan leads AI projects focusing on IT operations self-healing strategies, strengthening internal AI capabilities.

2021 Q3: no updates

2021 Q2

1 updates

Partnership with Microsoft Azure to leverage IoT and machine learning to minimize downtime and increase productivity, marking significant enterprise data and analytics advancements.

2021 Q1: no updates

2020 Q4

1 updates

ExxonMobil began focusing on edge AI initiatives and early AI networking equipment since the 1980s, with partnerships including Intel to explore advanced computing at the edge.