AI in Oil and Gas Market Size Worth USD 25.24 Bn by 2034 Driven by Predictive Maintenance and Operational Automation
According to Precedence Research, the AI in oil and gas market size is expected to be worth USD 25.24 billion by 2034, increasing from USD 7.64 billion in 2025 and is projected to grow at a solid CAGR of 14.2% from 2025 to 2034. Oil and gas firms accelerate their digital transformation, and artificial intelligence (AI) is emerging as a game-changer in the sector.
Ottawa, Aug. 04, 2025 (GLOBE NEWSWIRE) -- In terms of revenue, the global artificial intelligence (AI) in oil and gas market was valued at USD 6.69 billion in 2024, grew to USD 7.64 billion in 2025. It is predicted to rise from USD 8.73 billion in 2026 to approximately USD 25.24 billion by 2034. This surge is driven by the need for enhanced safety, predictive maintenance, and cost-efficiency in high-stakes operations.
In terms of CAGR, the market of AI in oil and gas is expanding at a double-digit CAGR of 14.2% from 2025 to 2034. The growing demand for enhancing operational efficiency in the sector drives the market growth.
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Artificial Intelligence in Oil and Gas Market Overview & Insights:
The AI in Oil and Gas Market is rapidly evolving as energy companies seek to enhance operational efficiency, safety, and profitability in a volatile and resource-intensive industry. AI technologies such as machine learning, computer vision, natural language processing, and predictive analytics are being integrated across upstream, midstream, and downstream segments to improve decision-making, reduce human error, and lower costs.
In upstream exploration and drilling, AI is enabling faster seismic data interpretation, reservoir modeling, and real-time drilling optimization. In midstream operations, AI supports predictive maintenance of pipelines, logistics optimization, and failure detection in transport systems. In the downstream segment, AI enhances refining processes, automates quality control, and personalizes customer engagement at retail fuel stations.
AI is no longer a luxury but a necessity in the oil and gas industry,” said Shivani Zoting, Principal Consultant at Precedence Research. “With growing pressure to optimize costs and reduce downtime, companies are aggressively adopting AI for predictive maintenance and operational automation.
How is AI Being Utilized in Oil & Gas Industry?
Artificial intelligence in the oil & gas sector is a process of using AI technologies in the oil & gas sector to enhance sustainability, efficiency, and safety. Artificial intelligence is used in various processes like distribution, exploration, refining, and many more in the oil & gas sector. AI helps in identifying potential oil & gas reserves by analyzing seismic data.
AI is widely used in various applications like defect detection, drilling optimization, and supply chain optimization in the oil & gas sector. AI helps in increasing efficiency, enhancing productivity, reducing energy consumption, improving safety, making better decisions, and enhancing sustainability.
Artificial Intelligence Use in Oil & Gas Companies
| Company Name | AI Use |
| ExxonMobil |
|
| Royal Dutch Shell |
|
| Chevron |
|
| British Petroleum |
|
| Saudi Aramco |
|
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️ Case Study: Chevron’s Predictive AI Transformation in Oilfield Operations
Chevron Corporation, a global energy giant, has long been at the forefront of technological innovation in the oil and gas sector. Faced with challenges including fluctuating oil prices, aging infrastructure, and a mandate for enhanced safety and environmental compliance, Chevron invested heavily in Artificial Intelligence starting in 2021. Their goal: to transform upstream operations through predictive insights, real-time monitoring, and optimization.
AI Deployment Strategy
Chevron partnered with tech leaders such as Microsoft (Azure AI) and C3.ai to build an enterprise AI platform capable of ingesting real-time data from thousands of IoT sensors embedded across its wellheads, compressors, pipelines, and rigs.
Key AI Technologies Used:
- Predictive Maintenance via machine learning to detect early signs of equipment wear and tear.
- Digital Twin Models for simulating oilfield performance.
- Natural Language Processing (NLP) to extract insights from unstructured technical reports.
- Deep Learning Algorithms to enhance seismic data interpretation and reservoir modeling.
Implementation and Impact
Pilot Deployment:
In 2022, Chevron deployed AI-driven predictive maintenance at its Permian Basin field—a highly productive but complex oilfield in Texas.
Measurable Outcomes:
- Reduced unplanned equipment downtime by 25% in the first year.
- Extended equipment life cycles by 18%, saving millions in deferred capex.
- Achieved 15% improvement in overall production efficiency through real-time optimization.
- Reduced methane leaks and improved compliance by using AI-powered drone inspections and infrared imaging.
Broader Transformation
The success in the Permian Basin led to enterprise-wide rollout by 2024:
- AI is now integrated into cargo route optimization, refining processes, and supply chain demand forecasting.
- Chevron reports an estimated $900 million in operational savings over 3 years, directly attributed to AI initiatives.
“AI allows us to make better decisions, faster—turning billions of data points into actionable insights that protect people, the planet, and profitability.”
— Jay Johnson, EVP, Upstream, Chevron
Lessons for the Industry
Chevron’s journey underscores that:
- AI is not a plug-and-play solution; it requires robust data infrastructure, skilled talent, and change management.
- The highest ROI is seen when AI is aligned with core operational KPIs like uptime, safety, and yield.
- Partnerships with tech vendors and open data ecosystems accelerate innovation.
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Artificial Intelligence in Oil and Gas Market Opportunity:
What is the Opportunity for Artificial Intelligence (AI) in Oil and Gas Market?
Supply Chain Management Unlocks Opportunity
The increasing focus on transforming the supply chain management of the oil & gas sector increases the adoption of AI. It provides insights into logistic planning, demand forecasting, and inventory management that help in optimizing supply chain operations. The focus on better customer satisfaction, improving efficiency, and reducing costs fuels demand for AI.
The need for identifying disruption in the supply chain increases the adoption of AI’s predictive analysis. It analyses market trends, past data, and weather patterns, and helps in avoiding shortages. It helps in supply chain management from upstream operations to distribution, which supports market growth.
The growing need for resource allocation, optimization of transportation routes, and scheduling requires AI. The increasing focus on real-time visibility of supply chains fuels demand for AI. Supply chain management creates an opportunity for the growth of the artificial intelligence oil & gas market.
Artificial Intelligence (AI) in Oil and Gas Market Challenges and Limitations:
What is the Limitation for Artificial Intelligence (AI) in Oil and Gas Market?
High Implementation Cost Limits Adoption of AI in Oil & Gas Market
Despite several benefits of AI in the oil & gas sector, the high implementation cost restricts the market growth. Factors like the requirement of data management, acquisition, & integration, need for specialized expertise, cybersecurity challenges, and integration with systems require high implementation cost. The analysis, collection, and storage of data requires a data management & infrastructure system that increases the implementation cost. The need for expertise in software development, data science, and machine learning leads to higher implementation costs.
The integration with legacy systems requires modifications and upgrades, which increases the cost. The risk of cybersecurity requires monitoring and robust security measures, leading to higher implementation costs. The need for high costs for system integration, hardware, and software directly affects the market. The high implementation cost hampers the artificial intelligence (AI) in the oil & gas market.
AI in Oil and Gas Market Coverage:
| Report Attributes | Key Statistics |
| Market Size in 2024 | USD 6.69 Billion |
| Market Size in 2025 | USD 7.64 Billion |
| Market Size in 2030 | USD 14.84 Billion |
| Market Size in 2032 | USD 19.35 Billion |
| Market Size by 2034 | USD 25.24 Billion |
| Growth Rate (2025 to 2034) | CAGR of 14.2% |
| Leading Region in 2024 | North America (captured 39.13% of market share) |
| Base Year | 2024 |
| Forecast Period | 2025 to 2034 |
| Segments Covered | Component, Function, Application and Region |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
| Key Players | Microsoft Corporation, FuGenX Technologies Pvt. Ltd, IBM Corporation, C3.AI, Google LLC, NVIDIA Corp., Royal Dutch Shell PLC, PJSC Gazprom Neft, Huawei Technologies Co. Ltd, Intel Corporation, Neudax, Infosys Limited, and Others. |
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Artificial Intelligence in Oil and Gas Market Key Regional Analysis:
Which Region Dominated the Artificial Intelligence (AI) in Oil & Gas Market?
North America dominated the Artificial Intelligence (AI) in Oil & Gas Market in 2024. The well-established infrastructure for the extraction of oil & gas increases demand for AI solutions. The growing private companies and government investment in research & development in the oil & gas sector for the implementation of AI help the market growth. The growing production of oil & gas increases demand for AI solutions. The focus on enhancing operational efficiency and optimizing production and exploration in the oil & gas sector fuels demand for AI, driving the overall growth of the market.
U.S. AI in Oil and Gas Market Size and Forecast 2025 to 2034
How Big is the U.S. AI in Oil and Gas Market?
According to Precedence Research, the U.S. artificial intelligence (AI) in oil and gas market size was valued at USD 1.84 billion in 2024 and is estimated to grow from USD 2.12 billion in 2025 to USD 7.34 billion by 2034. The market is poised to grow at a CAGR of 14.8% from 2025 to 2034.
Why U.S. Stands Out:
- Dominated by innovation and early AI adoption across upstream, midstream, and downstream operations.
- Proven applications include predictive maintenance, real-time drilling analytics, reservoir modeling, and operational automation.
- Leading contributions from tech-forward energy companies such as Chevron, ExxonMobil, SLB, and early rollout of platforms like IBM Watsonx in 2024.
Adoption and Industry Impact in the U.S.
The oil industry is allocating approximately USD 3.1 billion in AI spending in 2024, representing under 5% of total capital expenditures. AI investment is projected to increase up to 80% within five years. (Source: https://www.barrons.com)
At CERAWeek 2025, U.S. firms like BP, Devon Energy, and Chevron showcased improved productivity thanks to AI: Devon reported a 25% increase in well lifespan, while Chevron uses AI‑driven drones for maintenance and monitoring. (Source: https://www.reuters.com)
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Why is Asia Pacific Growing in the Artificial Intelligence (AI) in Oil & Gas Market?
Asia Pacific is experiencing the fastest growth in the market during the forecast period. The increasing production activities and exploration in the oil & gas industry increase demand for AI solutions. The focus on digital transformation in the oil & gas sector fuels the adoption of AI solutions to improve operational efficiency. The increasing demand for cost savings and productivity gains helps in the market growth.
The demand for reducing downtime, potential equipment failures, and proactive maintenance increases the adoption of AI solutions. The increasing optimization of operations like refining, drilling, and production increases demand for AI solutions. The growing adoption of AI across applications like downstream, upstream, and midstream drives the overall growth of the market.
Artificial Intelligence (AI) in Oil and Gas Market Segmentation Analysis
Component Analysis:
Why did Software Dominate the Artificial Intelligence (AI) in Oil & Gas Market?
The software segment dominated the Artificial Intelligence (AI) in oil & gas market in 2024. The presence of large amounts of data through diverse sources like seismic surveys, sensors, and drilling operations increases demand for software to identify correlations, patterns, and anomalies. The need for automating repetitive tasks like equipment monitoring, data entry, and report generation in the oil & gas sector increases demand for AI software.
The focus on extending critical equipment lifespans, preventing unexpected downtime, and reducing maintenance costs requires AI software. The growing demand for software for applications like ensuring compliance, monitoring worker safety, and detecting potential hazards drives the market growth.
Function Analysis:
How Predictive Maintenance Segment Held the Largest Share in the Artificial Intelligence (AI) in Oil & Gas Market?
The predictive maintenance segment held the largest revenue share in the Artificial Intelligence (AI) in oil & gas market in 2024. The focus on minimizing unplanned downtime in the oil & gas sector increases demand for predictive maintenance. The increasing demand for extending the lifespan of equipment and identifying issues of equipment early increases the adoption of predictive maintenance.
The focus on minimizing disruptions during planned downtime requires predictive maintenance. The increasing demand for predictive maintenance for optimizing maintenance schedules and enhancing operational efficiency in the oil & gas sector supports the overall growth of the market.
Application Analysis:
How Application Segment Dominates Artificial Intelligence (AI) in Oil & Gas Market?
The upstream segment dominated the Artificial Intelligence (AI) in oil & gas market in 2024. The growing demand for predictive equipment failures, improving operational efficiency, optimizing drilling, and reducing downtime in upstream applications increases demand for AI. The growing focus on extracting and finding oil & gas fuels adoption of AI. The growing utilization of AI functionalities like predictive maintenance in the upstream applications supports the market growth.
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Artificial Intelligence (AI) in Oil and Gas Market Top Companies
- Microsoft Corporation
- FuGenX Technologies Pvt. Ltd
- IBM Corporation
- C3.AI
- Google LLC
- NVIDIA Corp.
- Royal Dutch Shell PLC
- PJSC Gazprom Neft
- Huawei Technologies Co. Ltd
- Intel Corporation
- Neudax
- Infosys Limited
Recent Developments
- In September 2024, Huawei launched an AI application for oil & gas upstream. Innovation aims to increase production & reserves, achieve high-quality development, enhance industrial quality with intelligence, and ensure safe operations. The focus is on enhancing security, reducing cost, and boosting operational efficiency. (Source: https://e.huawei.com)
- In September 2024, APA Corporation collaborated with Palantir to use AI technology for oil & gas operations. The Palantir focuses on the development of software for supply chain management, production optimization, operational planning, maintenance planning, and contract management. The company’s AI solution helps in optimizing raw material logistics, improving equipment reliability, and AIP in invoice & contract documents. (Source: https://www.businesswire.com)
- In July 2024, Indosat launched AI solutions for the upstream oil & gas industry. The solution is cloud-based and helps in predictive maintenance for equipment and condition-based monitoring. The solution is used to improve collaborations among workers and monitor workplace safety. (Source: https://developingtelecoms.com/)
Artificial Intelligence (AI) in Oil and Gas Market Segments Covered in the Report
By Component
- Software
- Hardware
- Services
By Function
- Predictive Maintenance
- Machinery Inspection
- Material Movement
- Production Planning
- Field Services
- Quality Control
- Reclamation
By Application
- Upstream
- Midstream
- Downstream
By Region
- North America
- U.S.
- Canada
- Europe
- Germany
- UK
- France
- Italy
- Spain
- Sweden
- Denmark
- Norway
- Asia Pacific
- China
- Japan
- India
- South Korea
- Thailand
- Latin America
- Brazil
- Mexico
- Argentina
- Middle East & Africa
- South Africa
- UAE
- Saudi Arabia
- Kuwait
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