AI in Oil and Gas Market Size, Share & Industry Trends Analysis Report By Operation, By Component, By Regional Outlook and Forecast, 2022 - 2028

The Global AI in Oil and Gas Market size is expected to reach $5.2 billion by 2028, rising at a market growth of 13.2% CAGR during the forecast period.

The fastest-growing general-purpose technology of the modern age is artificial intelligence (AI), which has enormous potential for growth and innovation. AI has already resulted in significant modifications and altered the competition rules in the fields of industrial, healthcare, transport, retail, media, and finance.



Companies in these sectors now generate value by utilizing AI solutions rather than depending on conventional, human-centered business processes. The value creation process is driven by sophisticated algorithms that have been trained on substantial and meaningful datasets and are constantly fed new data. However, businesses outside of those with a strong internet presence can also benefit from AI.

Companies in the mining, oil, gas, and construction industries were late adopters of digitization, but they now rely more and more on AI solutions. Although the oil and gas sector first investigated using AI in the 1970s, the sector only recently began to seek more aggressive AI application prospects. It corresponds with the industry's shift toward the Oil and Gas 4.0 idea, whose main objective is to increase value through cutting-edge digital technology, and the exponential rise of AI capabilities.

Oil and gas businesses' main goal with AI (and other digitalization efforts) is to increase efficiency because they adopt new technologies much more quickly than they experiment with and alter their business strategies. In actuality, that usually means reducing risks and speeding up processes.  The application of artificial intelligence (AI) and machine learning technologies in the oil and gas industry has attracted a lot of attention during the last ten years.

This has caused the market for artificial intelligence in this sector to expand. Due to the rising difficulties, the oil and gas sector has had in the past when it comes to the discovery and production of hydrocarbons, a cross-disciplinary strategy is being used, necessitating the semi-automation and complete automation of several crucial operations. Every step of the exploration process, including geology, geophysical, and reservoir engineering, is being automated with artificial intelligence.



The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The below illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.

COVID-19 Impact Analysis

Demand for oil and gas decreased as a result of the COVID-19 pandemic and lockdowns. For instance, the International Energy Agency estimates that the oil demand declined by million barrels per day by the second quarter of 2020. However, in these exceptional conditions, AI use in the oil and gas sector has greatly expanded. In many facets of society, this crisis had several direct and indirect repercussions. To monitor and contain the virus pandemic in the interim, the digital and artificial intelligence industries can be a valuable professional resource.

Market Growth Factors

The Analysis And Improvement Of Data, As Well As The Identification Of Faults

The oil and gas business encounters numerous difficulties in identifying improper threading in pipes and flaws in devices that are prone to error. The production line later discovers the flaws that were not discovered before. This results in greater damages and losses and comes at a high cost to a business. However, it becomes simple to assess the quality of output when using AI and implementing a computer-vision-based system. Additionally, it offers thorough details on analytics flaws.

Utilize Analytics To Lower Production And Maintenance Costs And Improve Decision-Making

Oil and gas are kept in a central repository after extraction. It is then distributed by pipelines from there. Different temperatures and weather conditions cause oil and gas components to deteriorate and corrode, which can weaken the condition of the pipeline and result in faded threading. One of the main issues facing the sector is this. To prevent unfavorable outcomes, the oil and gas business must proactively address these concerns. The industry may help to stop any such incidents from happening by integrating AI solutions.

Market Restraining Factors

Lacking Competent Professionals In Ai Technology

An extremely advanced solution, the AI processor demands a high level of education and skills to operate. Artificial intelligence has quickly become popular among humans in recent years. People throughout the world use applications of artificial intelligence in their daily lives, such as self-driving automobiles and restaurant robots that serve food. For instance, robotic research is used in many different fields, such as security, healthcare, space exploration, and a plethora of other scientific fields.

Component Outlook

On the basis of Components, the AI in Oil and Gas Market is segmented into Solutions and Services. The service segment witnessed a significant revenue share in the AI in Oil and Gas Market in 2021. AI Services is a group of services with ready-made machine learning that simplify the deployment of AI to software and business processes for developers.

Operation Outlook

Based on the Operation, the AI in Oil and Gas Market is divided into Upstream, Midstream, and Downstream. The upstream segment garnered the largest revenue share in the AI in Oil and Gas Market in 2021. It involves looking for possible raw natural gas and crude oil reserves that are underground or beneath the sea, drilling test wells, and then drilling and running the wells that will bring the raw natural gas or crude oil to the surface.

Regional Outlook

Region-wise, the AI in Oil and Gas Market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region procured the highest revenue share in the AI in Oil and Gas Market in 2021. Due to the demand for AI in the oil and gas industry is anticipated to be driven by elements including the region's robust economy, the high adoption rate of AI technologies among oilfield operators and service providers, a strong presence of leading AI software and system providers, and merged investment by government and private organizations for the growth and development of R&D activities.

Cardinal Matrix - AI in Oil and Gas Market Competition Analysis

The major strategies followed by the market participants are Partnerships and Acquisitions. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation are the forerunners in the AI in Oil and Gas Market . Companies such as Intel Corporation, Cisco Systems, Inc., NVIDIA Corporation are some of the key innovators in AI in Oil and Gas Market .

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Oracle Corporation, Intel Corporation, IBM Corporation, Cisco Systems, Inc., Accenture PLC, NVIDIA Corporation, Cloudera, Inc., C3.ai, Inc. and FuGenX Technologies (USM Business Systems, Inc.).

Strategies deployed in AI in Oil and Gas Market

; Partnerships, Collaborations and Agreements:

• Apr-2022: Microsoft came into a partnership with Bharat Petroleum Corporation, the leading oil and Gas Company in India. Together, the companies aimed to open the possibilities that Microsoft's cloud delivers to manage the special difficulties of the oil and gas sector, allowing BPCL to boost the modernization of its tech architecture. Additionally, this is expected to improve and redefine the consumer experience.
• Mar-2022: Cloudera partnered with Kyndryl, American multinational information technology. Through this partnership, the companies aimed to support consumers allow and push their mission-critical multi-cloud, hybrid cloud, and edge computing data industries. Additionally, a joint innovation center to create combined industry keys and delivery abilities developed to enable consumers to boost their motion and migration to the cloud platform and environment of their choice.
• Nov-2021: IBM joined hands with Amazon Web Services, a subsidiary of Amazon. Together, the companies aimed to integrate the advantages of IBM Open Data for Industries for IBM Cloud Pak for Data and the AWS Cloud to benefit energy consumers. Additionally, This complete solution is developed on Red Hat OpenShift and is expected to run on the AWS Cloud, streamlining the capacity for consumers to operate workloads in the AWS cloud and on-premises.
• Sep-2021: C3 AI came into a partnership with Baker Hughes, an energy technology company. Through this partnership, the companies aimed to deploy the BHC3 Production Optimization enterprise AI application at MEG Energy, an Alberta, Canada -based energy firm, to enhance operational effectiveness, and productivity, and to nicely envision threats across the company’s upstream production procedures. Moreover, BHC3’s advanced business AI-based solutions is expected to further promote the differentiated, proprietary technology leverage to secure safe, sustainable production of energy.
• Jun-2021: C3 AI formed a partnership with Snowflake, the Data Cloud Company. This partnership aimed to integrate Snowflake’s unique architecture which permits consumers to run their data platforms smoothly across numerous clouds and regions at scale. Additionally, with C3 AI’s robust corporation AI development offering and family of industry-specific firm AI, applications businesses can instantly boost and emanate economic value from their data and business AI ambitions.
• Apr-2021: Accenture joined hands with Bharat Petroleum Corporation, the greatest oil and gas company in India. Through this collaboration, the companies aimed to convert India’s second-largest oil and gas business by digitally reimagining its comprehensive sales and distribution network. Moreover, Accenture is expected to use its abilities in artificial intelligence, data, and cloud technologies to design, build, and execute a digital platform, called IRIS.

; Product Launches and Product Expansions:

• Jun-2022: NVIDIA expanded its partnership with Siemens, a German multinational conglomerate corporation. This expansion aimed to allow the industrial metaverse and advance the utilization of AI-driven digital twin technology that is expected to assist in obtaining industrial automation to a new deck. Additionally, The companies intend to combine Siemens Xcelerator, the open digital business platform, and NVIDIA Omniverse, a medium for 3D design and teamwork. Moreover, This is expected to allow an industrial metaverse with physics-based digital samples from Siemens and real-time AI from NVIDIA in which businesses make conclusions faster and with improved confidence.
• Mar-2022: NVIDIA introduced an update to its AI platform to unveil its AI Accelerated program. NVIDIA’s AI platform is a software offering for advancing workloads, including recommender system, speech, and hyper-scale belief. Moreover, NVIDIA AI is the software toolbox of the world’s AI society, from AI data scientists and researchers to data and machine learning procedures sections.
• Nov-2021: Oracle introduced Oracle Cloud Infrastructure AI services, a cluster of services. The new OCI AI services provide designers the option of utilizing out-of-the-box models that have been prepared on business-based data or traditional training the services based on their firm's data.
• Jun-2021: IBM along with Schlumberger unveiled the industry’s first commercial hybrid cloud Enterprise Data Management Solution for the OSDU Data Platform. The new solution is expected to deliver energy operators with complete interoperability, creating their data available by any application within their exploration to production conditions through the OSDU common data standard to allow comfortable sharing of information between teams. Additionally, the solution is engineered to decrease the time for data transfers between applications to provide smaller costs along with enhanced decision making.
• Mar-2020: Accenture along with SAP unveiled SAP S/4HANA Cloud. The new SAP S/4HANA Cloud solution for lifts oil and gas helps customers to further enhance transparency into processes and cash flow. Additionally, the companies are providing a solution that conveys innovative technologies such as AI to provide greater visibility, real-time insights, and adequate decision-making.

; Acquisitions and Mergers:

• Aug-2022: Accenture completed the acquisition of Tenbu, a cloud data business that specializes in solutions for intelligent decision-making. This acquisition aimed to expand Accenture's abilities to assist businesses to steer new services, development, and stability by utilizing data from the cloud continuum for intelligent decision-making.
• Mar-2022: Microsoft took over Nuance Communications, a leader in conversational AI and ambient intelligence. This acquisition is expected to allow alliances across industries to boost their company goals with security-focused, cloud-based solutions ingrained with powerful, vertically optimized AI. Additionally, Consumers is expected to profit from an improved clinician, patient, consumer, and employee experiences, and eventually enhanced productivity and financial performance.
• Feb-2022: IBM completed the acquisition of Neudesic, a US-based cloud services consultancy. With this acquisition, the company aimed to extend IBM’s offering of hybrid multi-cloud services and additional passage of the enterprise’s AI strategy and hybrid cloud.
• Oct-2021: Cisco completed the acquisition of Epsagon, a privately held, modern observability company. Through this acquisition, Epsagon’s technology with Cisco’s dream to allow businesses to provide unmatched application experiences via industry-leading solutions with serious industry context. Moreover, by linking and contextualizing visibility and insights around the complete stack, teams can enhance collaboration to better understand their systems, solve issues fast, optimize and ensure application incidents and satisfy their consumers.
• Oct-2021: Accenture took over BRIDGEi2i, a Bengaluru-based AI and analytics company. Through this acquisition, the company aimed to further improve its AI skills and data science abilities to reinforce how enterprise global network provides value for consumers.
• Mar-2021: Cisco took over Acacia Communications, an optical networking strategy, and technology business. This acquisition is expected to strengthen Cisco’s responsibility to optics as a crucial building block that is expected to improve Cisco’s Internet for the Future process with supreme coherent optical solutions for consumers, also allowing them to manage the unprecedented scale of current IT.

; Geographical Expansions:

• Jun-2022: Intel India expanded its geographical footprints by establishing the design and engineering of a new state-of-the-art building in Bengaluru. The new addition accommodates 2,000 workers and is expected to help promote cutting-edge innovation and engineering work in client, artificial intelligence, data center, graphics, IoT, and automotive segments.

Scope of the Study

Market Segments Covered in the Report:

By Operation

• Upstream
• Midstream
• Downstream

By Component

• Solution
• Services

By Geography

• North America
• US
• Canada
• Mexico
• Rest of North America
• Europe
• Germany
• UK
• France
• Russia
• Spain
• Italy
• Rest of Europe
• Asia Pacific
• China
• Japan
• India
• South Korea
• Singapore
• Malaysia
• Rest of Asia Pacific
• LAMEA
• Brazil
• Argentina
• UAE
• Saudi Arabia
• South Africa
• Nigeria
• Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

• Microsoft Corporation
• Oracle Corporation
• Intel Corporation
• IBM Corporation
• Cisco Systems, Inc.
• Accenture PLC
• NVIDIA Corporation
• Cloudera, Inc.
• C3.ai, Inc.
• FuGenX Technologies (USM Business Systems, Inc.)

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