Report Code: CMI18025

Published Date: September 2022

Pages: 220+

Category: Next Generation Technologies

Report Snapshot

CAGR: 12.5%
2,194.9M
2021
2,583.2M
2022
5,689.7M
2030

Source: CMI

Study Period: 2024-2033
Fastest Growing Market: Asia-Pacific
Largest Market: Europe

Major Players

  • IBM
  • AI
  • Google LLC
  • Microsoft Corporation
  • Others

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Reports Description

According to Research Study published by Custom Market Insights (CMI), The global AI in oil and gas market has presented a growth of USD 2,194.9 million in 2021 and is expected to touch USD 5,689.7 million by the end of 2030 at a compound annual growth rate of 12.5% during the forecast period. This is expected to grow further due to the increasing demand for artificial intelligence among the various sectors worldwide.

Artificial intelligence in the oil and gas industry has become a major step taken by industries all over the world which helps to maintain the quality of the machinery with the help of artificial intelligence and prediction provided by the software systems that are utilized for judging the condition of the equipment. The inspection of machinery is also carried out with the help of software and artificial intelligence that informs regarding the fundamental end dynamic condition of the devices and hence helps in continuing the functions of the industry seamlessly without any problems.

The introduction of artificial intelligence into the oil and gas industry has helped to maintain the quality of the products by constantly keeping a check on the condition of the instruments and devices used in the industry. That official intelligence also takes care of the total output produced by improving the quality of gas and oil manufactured in the company. The quality of the final product is kept under strict check and hence provides the potential consumer with better products.

The entire system is explored with the help of artificial intelligence and can be checked for faults and defects in the various parts of the machinery which makes it quite comfortable for the technicians to go through the exact problem that has been created in the system. The capacity of the reservoir and tank are monitored with the help of artificial intelligence which helps the company to keep a check on the amount of gas or oil that is filled and collected in the storage units. The outbreak of the COVID pandemic had a considerable impact on the oil and gas market pertaining to the increasing rates of fuel and crude oil which hampered the demand and supply chain of these products.

The various restrictions which were imposed on the sale and supply of oil and gas during the period of the pandemic had a negative impact on the profit margin that the key market players owned. As the sales and demand were hampered the usage of artificial intelligence also saw a declining phase during the phase of the pandemic.

Growth Factors

A number of different tools and equipment are required for setting up the machinery which is required for artificial intelligence which imposes an additional demand for skilled professionals in the industry. The rapid advancements which have taken place in the field of machinery and technology have profited the development of artificial intelligence as well and have hence increased the confidence of key market players over the system. Numerous companies all over the world who deal in oil and gas consider the usage of artificial intelligence for managing the demand and supply chain as well as the various other functions that are included in the business.

The complex process of maintaining records and accounts of the sales and demand that have been conducted by the industry is managed easily with the help of artificial intelligence which provides accurate results and hence helps the company to maintain an accurate balance sheet. Probable chances of error that come into play when the systems are handled by human beings have been replaced with the help of artificial intelligence which provides maximum precision and accuracy in each and every field where it is applied. the use of artificial intelligence in the oil and gas industry has also reduced the total cost of production as the number of human beings employed to control the functions of the machinery has been reduced to a great extent. This helps to reduce the total expenditure made by the industry on managing advanced equipment and devices. Hence the profit margin which is earned by the oil and gas industries has increased tremendously over the period of time.

The huge amount of money that is spent on hiring skilled professionals emerges to be very costly for the key market players and hence the emergence of artificial intelligence into the oil and gas system has proved to be a suitable option for saving the excess expense that was made on hiring employees. Various opportunities have been created for artificial intelligence in the oil and gas industries with the support of the government which has helped to increase the total revenue return obtained by the key market players. Rapid research and development programs that are carried out by the key market players with a view to introducing advanced artificial intelligence systems into the oil and gas industry have helped the market to record a considerable revenue over the period of time which is expected to increase in the future as well.

Global Artificial Intelligence (AI) in Oil and Gas Market 2023 – 2032 (By Component)

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Segmental Insights

Segmentation of artificial intelligence in the oil and gas market on the basis of Component

On the basis of components, the segment of solutions has emerged as one of the fastest growing markets pertaining to the increasing demand for various advanced solutions that are available in the market provided by the key market players. The increasing demand for better services provided by artificial intelligence that helps to increase the speed of production and manufacturing has emerged as a major opportunity for the growth of the market which is expected to increase in a similar fashion in the future as well which will help the market to record a considerable revenue over the period of time.

The huge client base which has adopted the use of artificial intelligence for oil and gas industries has emerged as a potential consumer which has contributed significantly to the growth of the market. Increasing complexities regarding the rules and regulations imposed by the government on the manufacturer of oil and gas have provided great opportunities for the use of artificial intelligence.

The segment of services has also performed tremendously over the period of time owing to the increasing number of clients who have started using artificial intelligence for oil and gas production. The huge number of industries that are demanding advanced solutions all over the world has proved to be a major driving force for the growth of this particular segment over a period of time. The increasing demand and supply of gas and oil all over the world has boosted the economy of this particular sector tremendously.

Global Artificial Intelligence (AI) in Oil and Gas Market 2023 – 2032 (By Service Type)

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Segmentation of artificial intelligence in the oil and gas market on the basis of Operation

On the basis of operation, the segment upstream has emerged as a dominating market owing to its largest global share among all the competitors available in the market. This segment is foreseen to grow at a faster rate over the period of time pertaining to the increasing demand among the key market players and the ready acceptance of the use of modern technology and services that are provided by the constant research and development programs that are carried out all over the world hold stop the searching process for underground crude oil has emerged as a potential market for the upstream segment which is expected to grow further during the future as well and hence support the growth of the market considerably over the period of time.

The segment of midstream has also seen potential growth over the period of time pertaining to the huge client base it has received. The activities which are included under the midstream segment are processing storage and the transportation of the final petroleum products that are manufactured.

The outbreak of the pandemic had a considerable impact on the transportation facilities as they were hampered because of the strict rules and regulations that were imposed by the government with a view to restricting the spread of infection. The demand and supply chain of petroleum products was hampered tremendously as the consumer base was narrowed pertaining to the rules and regulations that were imposed on the people regarding the sales and supply or purchase of petroleum products. The other companies which operate with the help of pipelines and ships also come under the midstream segment which has seen tremendous growth over the period of time.

Report Scope

Feature of the Report Details
Market Size in 2021 USD 2,194.9 Million
Projected Market Size in 2030 USD 5,689.7 Million
CAGR Growth Rate 12.5% CAGR (2022-2030)
Base Year 2023
Forecast Period 2024-2033
Prominent Players IBM, C3.AI, Google LLC, Microsoft Corporation, Oracle, FuGenX Technologies Pvt. Ltd, Cloudera, Cisco Systems, NVIDIA Corporation, Intel Corporation and Others
Key Segment By Component, Operation and Region
Report Coverage Revenue Estimation and Forecast, Company Profile, Competitive Landscape, Growth Factors and Recent Trends
Regional Scope North America, Europe, Asia Pacific, Middle East & Africa, and South & Central America
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Regional Insights

On the basis of geography, the region of North America has emerged as the largest global market pertaining to the huge amount of oil and gas that has been produced over the period of time which has been assisted with the help of artificial intelligence in almost every field and process that has been included for the manufacturing of these products.

The huge number of companies that make use of artificial intelligence in this particular region has emerged as a major driving force for the growth of the AI in oil and gas market over the period of time which is expected to grow further in a similar fashion. The huge amount of gas and oil that has been exported to other countries all over the world has emerged as another major growth factor for the implementation of artificial intelligence into the system which helps to maintain a perfect record and manage the system by maintaining accuracy and precision.

The intrusion of artificial intelligence into the system of oil and gas has helped the companies to explore more areas all over the country and find out suitable locations for maximum extraction of oil and gas which has helped them to increase the revenue return over the period of time.

Global Artificial Intelligence (AI) in Oil and Gas Market 2023 – 2032 (By Million)

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Key Market Players

  • IBM
  • AI
  • Google LLC
  • Microsoft Corporation
  • Oracle
  • FuGenX Technologies Pvt. Ltd
  • Cloudera
  • Cisco Systems
  • NVIDIA Corporation
  • Intel Corporation

Recent developments

  • November 2021 – shell landed in collaboration with Infosys with a view to introducing a new product for the consumers. Leveraging solutions that provide artificial intelligence helps the company to modernize the various inventories that are used in the warehouse. The planning and development that will take place in the industries will help to reduce the amount of Labor and time that is required for conducting the maintenance operations.

Segments covered in the report

By Component

  • Services
  • Solutions

By Operation

  • Mainstream
  • Upstream
  • Downstream

By Service Type

  • Professional Services
  • Managed Services

On the basis of Geography

North America

  • U.S.
  • Canada
  • Mexico
  • Rest of North America

Europe

  • Germany
  • France
  • U.K.
  • Italy
  • Spain
  • Rest of Europe

Asia Pacific

  • China
  • Japan
  • India
  • New Zealand
  • Australia
  • South Korea
  • Rest of Asia Pacific

The Middle East & Africa

  • Saudi Arabia
  • UAE
  • Egypt
  • Kuwait
  • South Africa
  • Rest of the Middle East & Africa

Latin America

  • Brazil
  • Argentina
  • Rest of Latin America

Table of Contents

  • Chapter 1. Preface
    • 1.1 Report Description and Scope
    • 1.2 Research scope
    • 1.3 Research methodology
      • 1.3.1 Market Research Type
      • 1.3.2 Market research methodology
  • Chapter 2. Executive Summary
    • 2.1 Global AI in Oil and Gas Market, (2022 – 2030) (USD Million)
    • 2.2 Global AI in Oil and Gas Market: snapshot
  • Chapter 3. Global AI in Oil and Gas Market – Industry Analysis
    • 3.1 AI in Oil and Gas Market: Market Dynamics
    • 3.2 Market Drivers
      • 3.2.1 Confidence of Key Market Players over the System
      • 3.2.2 Reduced the total cost of Production
    • 3.3 Market Restraints
    • 3.4 Market Opportunities
    • 3.5 Market Challenges
    • 3.6 Porter’s Five Forces Analysis
    • 3.7 Market Attractiveness Analysis
      • 3.7.1 Market attractiveness analysis By Component
      • 3.7.2 Market attractiveness analysis By Operation
  • Chapter 4. Global AI in Oil and Gas Market- Competitive Landscape
    • 4.1 Company market share analysis
      • 4.1.1 Global AI in Oil and Gas Market: company market share, 2021
    • 4.2 Strategic development
      • 4.2.1 Acquisitions & mergers
      • 4.2.2 New Product launches
      • 4.2.3 Agreements, partnerships, collaborations, and joint ventures
      • 4.2.4 Research and development and Regional expansion
    • 4.3 Price trend analysis
  • Chapter 5. Global AI in Oil and Gas Market – Component Analysis
    • 5.1 Global AI in Oil and Gas Market Overview: By Component
      • 5.1.1 Global AI in Oil and Gas Market share, By Component, 2021 and 2030
    • 5.2 Services
      • 5.2.1 Global AI in Oil and Gas Market by Services, 2022 – 2030 (USD Million)
    • 5.3 Solutions
      • 5.3.1 Global AI in Oil and Gas Market by Solutions, 2022 – 2030 (USD Million)
  • Chapter 6. Global AI in Oil and Gas Market – Operation Analysis
    • 6.1 Global AI in Oil and Gas Market Overview: By Operation
      • 6.1.1 Global AI in Oil and Gas Market share, By Operation, 2021 and 2030
    • 6.2 Mainstream
      • 6.2.1 Global AI in Oil and Gas Market by Mainstream, 2022 – 2030 (USD Million)
    • 6.3 Upstream
      • 6.3.1 Global AI in Oil and Gas Market by Upstream, 2022 – 2030 (USD Million)
    • 6.4 Downstream
      • 6.4.1 Global AI in Oil and Gas Market by Downstream, 2022 – 2030 (USD Million)
  • Chapter 7. AI in Oil and Gas Market – Regional Analysis
    • 7.1 Global AI in Oil and Gas Market Regional Overview
    • 7.2 Global AI in Oil and Gas Market Share, by Region, 2021 & 2030 (USD Million)
    • 7.3. North America
      • 7.3.1 North America AI in Oil and Gas Market, 2022 – 2030 (USD Million)
        • 7.3.1.1 North America AI in Oil and Gas Market, by Country, 2022 – 2030 (USD Million)
    • 7.4 North America AI in Oil and Gas Market, by Component, 2022 – 2030
      • 7.4.1 North America AI in Oil and Gas Market, by Component, 2022 – 2030 (USD Million)
    • 7.5 North America AI in Oil and Gas Market, by Operation, 2022 – 2030
      • 7.5.1 North America AI in Oil and Gas Market, by Operation, 2022 – 2030 (USD Million)
    • 7.6. Europe
      • 7.6.1 Europe AI in Oil and Gas Market, 2022 – 2030 (USD Million)
        • 7.6.1.1 Europe AI in Oil and Gas Market, by Country, 2022 – 2030 (USD Million)
    • 7.7 Europe AI in Oil and Gas Market, by Component, 2022 – 2030
      • 7.7.1 Europe AI in Oil and Gas Market, by Component, 2022 – 2030 (USD Million)
    • 7.8 Europe AI in Oil and Gas Market, by Operation, 2022 – 2030
      • 7.8.1 Europe AI in Oil and Gas Market, by Operation, 2022 – 2030 (USD Million)
    • 7.9. Asia Pacific
      • 7.9.1 Asia Pacific AI in Oil and Gas Market, 2022 – 2030 (USD Million)
        • 7.9.1.1 Asia Pacific AI in Oil and Gas Market, by Country, 2022 – 2030 (USD Million)
    • 7.10 Asia Pacific AI in Oil and Gas Market, by Component, 2022 – 2030
      • 7.10.1 Asia Pacific AI in Oil and Gas Market, by Component, 2022 – 2030 (USD Million)
    • 7.11 Asia Pacific AI in Oil and Gas Market, by Operation, 2022 – 2030
      • 7.11.1 Asia Pacific AI in Oil and Gas Market, by Operation, 2022 – 2030 (USD Million)
    • 7.12. Latin America
      • 7.12.1 Latin America AI in Oil and Gas Market, 2022 – 2030 (USD Million)
        • 7.12.1.1 Latin America AI in Oil and Gas Market, by Country, 2022 – 2030 (USD Million)
    • 7.13 Latin America AI in Oil and Gas Market, by Component, 2022 – 2030
      • 7.13.1 Latin America AI in Oil and Gas Market, by Component, 2022 – 2030 (USD Million)
    • 7.14 Latin America AI in Oil and Gas Market, by Operation, 2022 – 2030
      • 7.14.1 Latin America AI in Oil and Gas Market, by Operation, 2022 – 2030 (USD Million)
    • 7.15. The Middle-East and Africa
      • 7.15.1 The Middle-East and Africa AI in Oil and Gas Market, 2022 – 2030 (USD Million)
        • 7.15.1.1 The Middle-East and Africa AI in Oil and Gas Market, by Country, 2022 – 2030 (USD Million)
    • 7.16 The Middle-East and Africa AI in Oil and Gas Market, by Component, 2022 – 2030
      • 7.16.1 The Middle-East and Africa AI in Oil and Gas Market, by Component, 2022 – 2030 (USD Million)
    • 7.17 The Middle-East and Africa AI in Oil and Gas Market, by Operation, 2022 – 2030
      • 7.17.1 The Middle-East and Africa AI in Oil and Gas Market, by Operation, 2022 – 2030 (USD Million)
  • Chapter 8. Company Profiles
    • 8.1 IBM
      • 8.1.1 Overview
      • 8.1.2 Financials
      • 8.1.3 Product Portfolio
      • 8.1.4 Business Strategy
      • 8.1.5 Recent Developments
    • 8.2 C3.AI
      • 8.2.1 Overview
      • 8.2.2 Financials
      • 8.2.3 Product Portfolio
      • 8.2.4 Business Strategy
      • 8.2.5 Recent Developments
    • 8.3 Google LLC
      • 8.3.1 Overview
      • 8.3.2 Financials
      • 8.3.3 Product Portfolio
      • 8.3.4 Business Strategy
      • 8.3.5 Recent Developments
    • 8.4 Microsoft Corporation
      • 8.4.1 Overview
      • 8.4.2 Financials
      • 8.4.3 Product Portfolio
      • 8.4.4 Business Strategy
      • 8.4.5 Recent Developments
    • 8.5 Oracle
      • 8.5.1 Overview
      • 8.5.2 Financials
      • 8.5.3 Product Portfolio
      • 8.5.4 Business Strategy
      • 8.5.5 Recent Developments
    • 8.6 FuGenX Technologies Pvt. Ltd
      • 8.6.1 Overview
      • 8.6.2 Financials
      • 8.6.3 Product Portfolio
      • 8.6.4 Business Strategy
      • 8.6.5 Recent Developments
    • 8.7 Cloudera
      • 8.7.1 Overview
      • 8.7.2 Financials
      • 8.7.3 Product Portfolio
      • 8.7.4 Business Strategy
      • 8.7.5 Recent Developments
    • 8.8 Cisco Systems
      • 8.8.1 Overview
      • 8.8.2 Financials
      • 8.8.3 Product Portfolio
      • 8.8.4 Business Strategy
      • 8.8.5 Recent Developments
    • 8.9 NVIDIA Corporation
      • 8.9.1 Overview
      • 8.9.2 Financials
      • 8.9.3 Product Portfolio
      • 8.9.4 Business Strategy
      • 8.9.5 Recent Developments
    • 8.10 Intel Corporation
      • 8.10.1 Overview
      • 8.10.2 Financials
      • 8.10.3 Product Portfolio
      • 8.10.4 Business Strategy
      • 8.10.5 Recent Developments

List Of Figures

Figures No 1 to 19

List Of Tables

Tables No 1 to 52

Report Methodology

In order to get the most precise estimates and forecasts possible, Custom Market Insights applies a detailed and adaptive research methodology centered on reducing deviations. For segregating and assessing quantitative aspects of the market, the company uses a combination of top-down and bottom-up approaches. Furthermore, data triangulation, which examines the market from three different aspects, is a recurring theme in all of our research reports. The following are critical components of the methodology used in all of our studies:

Preliminary Data Mining

On a broad scale, raw market information is retrieved and compiled. Data is constantly screened to make sure that only substantiated and verified sources are taken into account. Furthermore, data is mined from a plethora of reports in our archive and also a number of reputed & reliable paid databases. To gain a detailed understanding of the business, it is necessary to know the entire product life cycle and to facilitate this, we gather data from different suppliers, distributors, and buyers.

Surveys, technological conferences, and trade magazines are used to identify technical issues and trends. Technical data is also gathered from the standpoint of intellectual property, with a focus on freedom of movement and white space. The dynamics of the industry in terms of drivers, restraints, and valuation trends are also gathered. As a result, the content created contains a diverse range of original data, which is then cross-validated and verified with published sources.

Statistical Model

Simulation models are used to generate our business estimates and forecasts. For each study, a one-of-a-kind model is created. Data gathered for market dynamics, the digital landscape, development services, and valuation patterns are fed into the prototype and analyzed concurrently. These factors are compared, and their effect over the projected timeline is quantified using correlation, regression, and statistical modeling. Market forecasting is accomplished through the use of a combination of economic techniques, technical analysis, industry experience, and domain knowledge.

Short-term forecasting is typically done with econometric models, while long-term forecasting is done with technological market models. These are based on a synthesis of the technological environment, legal frameworks, economic outlook, and business regulations. Bottom-up market evaluation is favored, with crucial regional markets reviewed as distinct entities and data integration to acquire worldwide estimates. This is essential for gaining a thorough knowledge of the industry and ensuring that errors are kept to a minimum.

Some of the variables taken into account for forecasting are as follows:

• Industry drivers and constraints, as well as their current and projected impact

• The raw material case, as well as supply-versus-price trends

• Current volume and projected volume growth through 2030

We allocate weights to these variables and use weighted average analysis to determine the estimated market growth rate.

Primary Validation

This is the final step in our report’s estimating and forecasting process. Extensive primary interviews are carried out, both in-person and over the phone, to validate our findings and the assumptions that led to them.
Leading companies from across the supply chain, including suppliers, technology companies, subject matter experts, and buyers, use techniques like interviewing to ensure a comprehensive and non-biased overview of the business. These interviews are conducted all over the world, with the help of local staff and translators, to overcome language barriers.

Primary interviews not only aid with data validation, but also offer additional important insight into the industry, existing business scenario, and future projections, thereby improving the quality of our reports.

All of our estimates and forecasts are validated through extensive research work with key industry participants (KIPs), which typically include:

• Market leaders

• Suppliers of raw materials

• Suppliers of raw materials

• Buyers.

The following are the primary research objectives:

• To ensure the accuracy and acceptability of our data.

• Gaining an understanding of the current market and future projections.

Data Collection Matrix

Perspective Primary research Secondary research
Supply-side
  • Manufacturers
  • Technology distributors and wholesalers
  • Company reports and publications
  • Government publications
  • Independent investigations
  • Economic and demographic data
Demand-side
  • End-user surveys
  • Consumer surveys
  • Mystery shopping
  • Case studies
  • Reference customers


Market Analysis Matrix

Qualitative analysis Quantitative analysis
  • Industry landscape and trends
  • Market dynamics and key issues
  • Technology landscape
  • Market opportunities
  • Porter’s analysis and PESTEL analysis
  • Competitive landscape and component benchmarking
  • Policy and regulatory scenario
  • Market revenue estimates and forecast up to 2028
  • Market revenue estimates and forecasts up to 2028, by technology
  • Market revenue estimates and forecasts up to 2028, by application
  • Market revenue estimates and forecasts up to 2028, by type
  • Market revenue estimates and forecasts up to 2028, by component
  • Regional market revenue forecasts, by technology
  • Regional market revenue forecasts, by application
  • Regional market revenue forecasts, by type
  • Regional market revenue forecasts, by component

Key Market Players

  • IBM
  • AI
  • Google LLC
  • Microsoft Corporation
  • Oracle
  • FuGenX Technologies Pvt. Ltd
  • Cloudera
  • Cisco Systems
  • NVIDIA Corporation
  • Intel Corporation
  • Others

FAQs

The “North America” region will lead the global AI in the oil and Gas market from 2022 to 2030.

The key players operating in AI in the Oil and Gas market are IBM, C3.AI, Google LLC, Microsoft Corporation, Oracle, FuGenX Technologies Pvt. Ltd, Cloudera, Cisco Systems, NVIDIA Corporation, Intel Corporation

The global AI in the Oil and Gas market is expanding growth with a CAGR of approximately 13.5% during the forecast period (2022 to 2030).

The global AI in the Oil and Gas market size was valued at USD 2.32 billion in 2021 and it is projected to reach around USD 7.99 billion by 2030.

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