What is the current market size and future outlook for the generative artificial intelligence (ai) in oil and gas market?
The generative artificial intelligence (AI) in oil and gas market size has grown rapidly in recent years. It will grow from $0.45 $ billion in 2024 to $0.53 $ billion in 2025 at a compound annual growth rate (CAGR) of 17.3%. The growth in the historic period can be attributed to efficiency improvements, exploration and production optimization, digital transformation initiatives, the need to reduce operational costs during periods of low oil prices, and the increasing volume of data generated by sensors and exploration activities.
The generative artificial intelligence (AI) in oil and gas market size is expected to see rapid growth in the next few years. It will grow to $0.99 $ billion in 2029 at a compound annual growth rate (CAGR) of 17.0%. The growth in the forecast period can be attributed to operational efficiency, optimization of resource extraction and management through ai-driven insights, environmental compliance, supply chain optimization, ai provides better risk assessment and mitigation strategies. Major trends in the forecast period include advanced predictive maintenance, ai-driven exploration, automated drilling optimization, advanced ai models assess and mitigate risks, and advanced supply chain management.
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How has the generative artificial intelligence (ai) in oil and gas market evolved, and what factors have shaped its growth?
An increasing shift towards cloud technologies is expected to propel the growth of generative AI in the oil and gas market going forward. Cloud technologies involve providing computing services such as storage, processing, and applications via the Internet rather than using local servers or personal devices. The rising demand for cloud technologies is driven by the need for scalable IT solutions, cost savings, better collaboration, and the increase in remote work and digital transformation. Cloud technologies support generative AI in oil and gas by offering the computational power and storage needed to handle large data sets, leading to better predictive analytics, optimized resource extraction, and enhanced decision-making. For instance, in December 2023, according to Eurostat, a Luxembourg-based intergovernmental organization, 45.2% of EU enterprises purchased cloud computing services. Moreover, purchases of cloud computing services by EU enterprises increased by 4.2 percentage points in 2023 compared to 2021. Therefore, the increasing shift towards cloud technologies is driving the growth of generative AI in the oil and gas market.
What are the major segments of the generative artificial intelligence (ai) in oil and gas market?
The generative artificial intelligence (AI) in oil and gas market covered in this report is segmented –
1) By Deployment: On-Premise, Cloud-Based
2) By Function: Data Analysis And Interpretation, Predictive Modelling, Anomaly Detection, Decision Support, Other Functions
3) By Application: Asset Maintenance, Drilling Optimization, Exploration And Production, Reservoir Modelling, Other Applications
4) By End User: Oil And Gas Companies, Drilling Contractors, Equipment Manufacturers, Service Providers, Consulting Firms
Subsegments:
1) By On-Premise: Infrastructure Management, Data Security Solutions, Legacy System Integration, Customizable AI Models
2) By Cloud-Based: Software as a Service (SaaS), Data Storage and Analytics, Real-Time Monitoring Solutions, Scalable AI Solutions
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Which companies dominate the generative artificial intelligence (ai) in oil and gas market?
Major companies operating in the generative artificial intelligence (AI) in oil and gas market are Exxon Mobil Corporation, Google LLC, Chevron Corporation, TotalEnergies SE, Microsoft Corporation, Equinor ASA, Siemens AG, International Business Machines Corporation, Honeywell International Inc., ABB Ltd., Tata Consultancy Services Limited, Cognizant Technology Solutions Corporation, Infosys Limited, DXC Technology Company, Emerson Electric Co., Wipro Limited, Rockwell Automation Inc., AVEVA Group plc, Aspen Technology Inc., C3.ai Inc., Altair Engineering Inc.
How will evolving trends contribute to the growth of the generative artificial intelligence (ai) in oil and gas market?
Major companies operating in generative AI in the oil and gas market are increasingly adopting sophisticated AI technologies for data-driven decision-making, such as generative AI large language models, to enhance data analysis, optimize operational efficiency, and provide predictive insights for better decision-making. A generative AI large language model is an advanced AI that processes and produces 250 billion parameters, which allows for high flexibility and accuracy in generating outputs and making predictions. For instance, in March 2024, Saudi Aramco, a Saudi-Arabia-based oil and gas company, launched Aramco Metabrain AI. It is a large language model designed specifically for the oil and gas industry. It leverages decades of Aramco’s historical data and evaluates drilling plans, geological information, and past drilling performance to suggest the best well options. Additionally, it provides accurate forecasts for refined product prices, market trends, and geopolitical factors.
What are the key regional dynamics of the generative artificial intelligence (ai) in oil and gas market, and which region leads in market share?
North America was the largest region in the generative artificial intelligence in the oil and gas market in 2024. The regions covered in the generative artificial intelligence (AI) in oil and gas market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Does The Generative Artificial Intelligence (AI) In Oil And Gas Market Report 2025 Offer?
The generative artificial intelligence (ai) in oil and gas market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.
Generative artificial intelligence (AI) in the oil and gas industry refers to AI systems that can create new data, models, or insights based on existing information to improve decision-making, efficiency, and innovation. It helps forecast equipment failures, reservoir behavior, and production outcomes by creating advanced simulation models and enhances automation of routine tasks, such as data analysis and reporting, by creating adaptive and intelligent systems.
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