Artificial Intelligence in Oil & Gas Market by Component (Hardware, Services, Software), Function (Field Services, Material Movement, Predictive Maintenance & Machine Inspection), Application - Global Forecast 2024-2030
The Artificial Intelligence in Oil & Gas Market size was estimated at USD 2.93 billion in 2023 and expected to reach USD 3.35 billion in 2024, at a CAGR 14.28% to reach USD 7.47 billion by 2030.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Artificial Intelligence in Oil & Gas Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Artificial Intelligence in Oil & Gas Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the Artificial Intelligence in Oil & Gas Market, highlighting leading vendors and their innovative profiles. These include C3.ai, Inc., China Petrochemical Corporation, Cisco Systems, Inc., Flutura, FuGenX Technologies Pvt. Ltd., Infosys Limited, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, Saudi Arabian Oil Company, Seven Lakes Enterprises, Inc., Shell plc, SparkCognition, Inc., and TotalEnergies SE.
Market Segmentation & Coverage
This research report categorizes the Artificial Intelligence in Oil & Gas Market to forecast the revenues and analyze trends in each of the following sub-markets:
Component
Hardware
Field Services
Downstream
Americas
Argentina
California
Australia
Denmark
The report offers valuable insights on the following aspects:
- Market Penetration: It presents comprehensive information on the market provided by key players.
- Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
- Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
- Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
- Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
- What is the market size and forecast of the Artificial Intelligence in Oil & Gas Market?
- Which products, segments, applications, and areas should one consider investing in over the forecast period in the Artificial Intelligence in Oil & Gas Market?
- What are the technology trends and regulatory frameworks in the Artificial Intelligence in Oil & Gas Market?
- What is the market share of the leading vendors in the Artificial Intelligence in Oil & Gas Market?
- Which modes and strategic moves are suitable for entering the Artificial Intelligence in Oil & Gas Market?
Note: PDF & Excel + Online Access - 1 Year
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency & Pricing
- 1.5. Language
- 1.6. Limitations
- 1.7. Assumptions
- 1.8. Stakeholders
- 2. Research Methodology
- 2.1. Define: Research Objective
- 2.2. Determine: Research Design
- 2.3. Prepare: Research Instrument
- 2.4. Collect: Data Source
- 2.5. Analyze: Data Interpretation
- 2.6. Formulate: Data Verification
- 2.7. Publish: Research Report
- 2.8. Repeat: Report Update
- 3. Executive Summary
- 4. Market Overview
- 4.1. Introduction
- 4.2. Artificial Intelligence in Oil & Gas Market, by Region
- 5. Market Insights
- 5.1. Market Dynamics
- 5.1.1. Drivers
- 5.1.1.1. Rising need to decode complex data used for oil & gas explorations and production
- 5.1.1.2. Growing demand to monitor the safety and security standards of the work site
- 5.1.1.3. Demand for AI in upstream operations
- 5.1.2. Restraints
- 5.1.2.1. High cost of investment in installation
- 5.1.3. Opportunities
- 5.1.3.1. Application of AI to test potential new developments and to access the environmental impacts of new projects
- 5.1.3.2. Increasing research and development to explore cognitive computing and machine learning in oil & gas sector
- 5.1.4. Challenges
- 5.1.4.1. Limited skilled professionals to manage AI systems
- 5.2. Market Segmentation Analysis
- 5.3. Market Trend Analysis
- 5.4. Cumulative Impact of High Inflation
- 5.5. Porter’s Five Forces Analysis
- 5.5.1. Threat of New Entrants
- 5.5.2. Threat of Substitutes
- 5.5.3. Bargaining Power of Customers
- 5.5.4. Bargaining Power of Suppliers
- 5.5.5. Industry Rivalry
- 5.6. Value Chain & Critical Path Analysis
- 5.7. Regulatory Framework
- 6. Artificial Intelligence in Oil & Gas Market, by Component
- 6.1. Introduction
- 6.2. Hardware
- 6.3. Services
- 6.4. Software
- 7. Artificial Intelligence in Oil & Gas Market, by Function
- 7.1. Introduction
- 7.2. Field Services
- 7.3. Material Movement
- 7.4. Predictive Maintenance & Machine Inspection
- 7.5. Production Planning
- 7.6. Quality Control
- 7.7. Reclamation
- 8. Artificial Intelligence in Oil & Gas Market, by Application
- 8.1. Introduction
- 8.2. Downstream
- 8.3. Midstream
- 8.4. Upstream
- 9. Americas Artificial Intelligence in Oil & Gas Market
- 9.1. Introduction
- 9.2. Argentina
- 9.3. Brazil
- 9.4. Canada
- 9.5. Mexico
- 9.6. United States
- 10. Asia-Pacific Artificial Intelligence in Oil & Gas Market
- 10.1. Introduction
- 10.2. Australia
- 10.3. China
- 10.4. India
- 10.5. Indonesia
- 10.6. Japan
- 10.7. Malaysia
- 10.8. Philippines
- 10.9. Singapore
- 10.10. South Korea
- 10.11. Taiwan
- 10.12. Thailand
- 10.13. Vietnam
- 11. Europe, Middle East & Africa Artificial Intelligence in Oil & Gas Market
- 11.1. Introduction
- 11.2. Denmark
- 11.3. Egypt
- 11.4. Finland
- 11.5. France
- 11.6. Germany
- 11.7. Israel
- 11.8. Italy
- 11.9. Netherlands
- 11.10. Nigeria
- 11.11. Norway
- 11.12. Poland
- 11.13. Qatar
- 11.14. Russia
- 11.15. Saudi Arabia
- 11.16. South Africa
- 11.17. Spain
- 11.18. Sweden
- 11.19. Switzerland
- 11.20. Turkey
- 11.21. United Arab Emirates
- 11.22. United Kingdom
- 12. Competitive Landscape
- 12.1. FPNV Positioning Matrix
- 12.2. Market Share Analysis, By Key Player
- 12.3. Competitive Scenario Analysis, By Key Player
- 13. Competitive Portfolio
- 13.1. Key Company Profiles
- 13.1.1. C3.ai, Inc.
- 13.1.2. China Petrochemical Corporation
- 13.1.3. Cisco Systems, Inc.
- 13.1.4. Flutura
- 13.1.5. FuGenX Technologies Pvt. Ltd.
- 13.1.6. Infosys Limited
- 13.1.7. Intel Corporation
- 13.1.8. International Business Machines Corporation
- 13.1.9. Microsoft Corporation
- 13.1.10. Oracle Corporation
- 13.1.11. Saudi Arabian Oil Company
- 13.1.12. Seven Lakes Enterprises, Inc.
- 13.1.13. Shell plc
- 13.1.14. SparkCognition, Inc.
- 13.1.15. TotalEnergies SE
- 13.2. Key Product Portfolio
- 14. Appendix
- 14.1. Discussion Guide
- 14.2. License & Pricing
- FIGURE 1. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET RESEARCH PROCESS
- FIGURE 2. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, 2023 VS 2030
- FIGURE 3. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, 2018-2030 (USD MILLION)
- FIGURE 4. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY REGION, 2023 VS 2030 (%)
- FIGURE 5. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY REGION, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 6. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET DYNAMICS
- FIGURE 7. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY COMPONENT, 2023 VS 2030 (%)
- FIGURE 8. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY COMPONENT, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 9. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY FUNCTION, 2023 VS 2030 (%)
- FIGURE 10. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY FUNCTION, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 11. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY APPLICATION, 2023 VS 2030 (%)
- FIGURE 12. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY APPLICATION, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 13. AMERICAS ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
- FIGURE 14. AMERICAS ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 15. UNITED STATES ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY STATE, 2023 VS 2030 (%)
- FIGURE 16. UNITED STATES ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY STATE, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 17. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
- FIGURE 18. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 19. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY COUNTRY, 2023 VS 2030 (%)
- FIGURE 20. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SIZE, BY COUNTRY, 2023 VS 2024 VS 2030 (USD MILLION)
- FIGURE 21. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET, FPNV POSITIONING MATRIX, 2023
- FIGURE 22. ARTIFICIAL INTELLIGENCE IN OIL & GAS MARKET SHARE, BY KEY PLAYER, 2023
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