Generative Artificial Intelligence (AI) in Oil and Gas Market Report 2024

This Generative Artificial Intelligence (AI) In Oil And Gas market report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.

The generative artificial intelligence in the oil and gas market size has grown rapidly in recent years. It will grow from $0.38 billion in 2023 to $0.45 billion in 2024 at a compound annual growth rate (CAGR) of 17%. The growth observed in the historic period can be linked to several factors, including enhancements in efficiency, optimization of exploration and production processes, digital transformation efforts, the drive to lower operational costs during times of reduced oil prices, and the growing amount of data generated from sensors and exploration activities.

The generative artificial intelligence in the oil and gas market size is expected to see rapid growth in the next few years. It will grow to $0.84 billion in 2028 at a compound annual growth rate (CAGR) of 17.1%. The anticipated growth during the forecast period can be attributed to several factors, including enhanced operational efficiency, optimization of resource extraction and management through AI-driven insights, environmental compliance, and supply chain optimization. AI also contributes to improved risk assessment and mitigation strategies. Key trends expected in the forecast period include advanced predictive maintenance, AI-driven exploration, automated drilling optimization, sophisticated AI models for risk assessment and mitigation, and enhanced supply chain management.

The growing adoption of cloud technologies is expected to drive the expansion of generative AI in the oil and gas sector. Cloud technologies offer computing services such as storage, processing, and applications over the Internet, rather than relying on local servers or personal devices. The surge in demand for cloud solutions is fueled by the need for scalable IT infrastructure, cost efficiency, improved collaboration, and the rise in remote work and digital transformation. By providing the necessary computational power and storage for handling large data sets, cloud technologies support generative AI in oil and gas, leading to enhanced predictive analytics, optimized resource extraction, and improved decision-making. For example, Eurostat reported in December 2023 that 45.2% of EU enterprises had purchased cloud computing services, with a 4.2 percentage point increase in such purchases from 2021 to 2023. This shift towards cloud technologies is therefore propelling the growth of generative AI in the oil and gas market.

Major players in the generative AI sector for oil and gas are increasingly utilizing advanced AI technologies for data-driven decision-making. Generative AI large language models, which can process and generate outputs with 250 billion parameters, are enhancing data analysis, operational efficiency, and predictive capabilities. For instance, in March 2024, Saudi Aramco introduced Aramco Metabrain AI, a large language model tailored for the oil and gas industry. This model uses Aramco’s extensive historical data to assess drilling plans, geological information, and past drilling performance to recommend optimal well options and forecast refined product prices, market trends, and geopolitical factors.

In May 2023, Shell plc partnered with SparkCognition to expedite the imaging and exploration of subsurface structures using generative AI technology. SparkCognition, a US-based firm specializing in AI-driven solutions, collaborates with oil and gas companies to enhance operational efficiency, reduce costs, and improve safety.

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.

North America was the largest region in the generative artificial intelligence in the oil and gas market in 2023. 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.

The countries covered in the generative artificial intelligence (AI) in oil and gas market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Generative artificial intelligence (AI) in the oil and gas sector involves AI systems capable of generating new data, models, or insights from existing information. This capability enhances decision-making, efficiency, and innovation by forecasting equipment failures, reservoir behavior, and production outcomes through advanced simulation models. It also improves the automation of routine tasks such as data analysis and reporting by developing adaptive and intelligent systems.

Generative AI in the oil and gas industry is primarily deployed either on-premise or in the cloud. On-premise solutions are installed and operated on a company's own hardware. These solutions handle various tasks such as data analysis, predictive modeling, anomaly detection, and decision support for applications including asset maintenance, drilling optimization, exploration and production, and reservoir modeling. These systems serve a range of users, including oil and gas companies, drilling contractors, equipment manufacturers, service providers, and consulting firms.

The generative artificial intelligence (AI) in oil and gas market research report is one of a series of new reports that provides generative artificial intelligence (AI) in oil and gas market statistics, including generative artificial intelligence (AI) in oil and gas industry global market size, regional shares, competitors with a generative artificial intelligence (AI) in oil and gas market share, detailed generative artificial intelligence (AI) in oil and gas market segments, market trends and opportunities, and any further data you may need to thrive in the generative artificial intelligence (AI) in oil and gas industry. This generative artificial intelligence (AI) in oil and gas market research report delivers a complete perspective on everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The generative artificial intelligence (AI) in oil and gas market consists of revenues earned by entities by providing services such as exploration and reservoir modeling, predictive maintenance, operational optimization, and supply chain management. The market value includes the value of related goods sold by the service provider or included within the service offering. The generative artificial intelligence (AI) in oil and gas market also includes sales of servers and computing hardware for AI processing, and sensors and IoT devices for data collection. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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