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 and machine learning technologies across its operations from 2020 through 2025, focusing on predictive maintenance, data unification, and workflow automation to optimize oil and gas production, reduce downtime, and increase operational efficiency.
  • Key figures such as Sarah Karthigan and Andrew Curry have led initiatives to expand AI applications, including self-healing IT operations and machine learning-driven production enhancements, contributing to ambitions like saving $15 billion in operating costs by 2027.
  • By 2024-2025, ExxonMobil notably pivoted toward powering AI data centers through natural gas plants with carbon capture, while also employing autonomous AI agents to reduce costs and emissions, signaling a broadened AI strategy encompassing operational excellence and energy transition leadership.

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6 AI Use Cases at ExxonMobil

Autonomous Operations
2025
Traditional
Generative
Agentic
Outcome
Costs
The company uses autonomous AI agents to optimize operations, reduce emissions, and cut costs, advancing its position in the energy transition and operational sustainability. [1]
Collaborative Design
2025
Traditional
Generative
Agentic
Outcome
Costs
ExxonMobil employs AI tools to accelerate engineering design collaboration on offshore rigs, improving communication and reducing project timelines. [1]
Energy Supply Optimization
2024
Traditional
Generative
Agentic
Outcome
Revenue
ExxonMobil applies AI to forecast and align energy production to meet the rising demands from data centers and AI infrastructure, including powering AI data centers with natural gas plants utilizing carbon capture technology. [1][2][3]
Safety Enhancement
2024
Traditional
Generative
Agentic
Outcome
Risk
Implementing AI for improved safety protocols, ExxonMobil leverages machine learning and computer vision to reduce workplace accidents and enhance occupational safety. [1]
Production Optimization
2024
Traditional
Generative
Agentic
Outcome
Revenue
By integrating AI-driven machine learning workflows, ExxonMobil enhances oil and gas well productivity, such as increasing Bakken field output by more than 5%. [1][2]
Predictive Maintenance
2023
Traditional
Generative
Agentic
Outcome
Costs
ExxonMobil uses AI to predict equipment failures and schedule maintenance proactively, reducing unplanned downtime and lowering labor costs across its operations. [1][2]

Timeline

2025 Q3

1 updates

ExxonMobil's AI strategy in 2025 employs autonomous AI agents to reduce costs and emissions and to maintain leadership in the energy transition, while continuing to scale oil and gas production to meet energy demands of AI and data centers globally.

2025 Q2: no updates

2025 Q1

1 updates

ExxonMobil partnered with CoLab Software to deploy AI-powered engineering design collaboration tools on offshore oil rigs, accelerating design and communication workflows.

2024 Q4

5 updates

ExxonMobil pushed strategic AI initiatives such as powering AI data centers with natural gas plants equipped with carbon capture, targeting a $15 billion reduction in operating costs by 2027. It also developed personalized customer service offerings through AI-driven analytics.

2024 Q3

1 updates

ExxonMobil used AI to build technology roadmaps helping to optimize oil and gas production across regions including Guyana and Australia.

2024 Q2

3 updates

ExxonMobil's machine learning workflow boosted output by over 5% in Bakken gas lift operations. The firm also enhanced safety protocols and reduced workplace accidents using AI technologies, with leadership insights from Andrew Curry about AI's future impacts.

2024 Q1: no updates

2023 Q4: no updates

2023 Q3

2 updates

The company implemented AI for predictive maintenance, achieving significant reductions in unplanned downtime and labor costs. ExxonMobil also developed a secure data strategy, delineating data readiness for advanced AI and ML use.

2023 Q2: no updates

2023 Q1

1 updates

ExxonMobil leveraged AI to integrate data silos and expedite well development, accelerating oil well deployment and improving operational efficiency.

2022 Q4: no updates

2022 Q3: no updates

2022 Q2: no updates

2022 Q1: no updates

2021 Q4

1 updates

Under the leadership of Sarah Karthigan, ExxonMobil focused on AI-driven self-healing strategies for IT operations, advancing automation and resilience in enterprise technology systems.

2021 Q3: no updates

2021 Q2

1 updates

Partnering with Microsoft Azure, ExxonMobil integrated IoT and machine learning to minimize equipment downtime and boost productivity, marking significant strides in enterprise data and analytics.

2021 Q1: no updates

2020 Q4

1 updates

ExxonMobil began AI-related exploration in earnest with early efforts dating back to the 1980s. In Q4 2020, it advanced edge computing initiatives by collaborating with Intel to leverage AI at the equipment level.