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市場調查報告書
商品編碼
1702030

2025-2033 年石油和天然氣市場人工智慧報告（按類型、功能、應用和地區）

AI in Oil and Gas Market Report by Type, Function, Application, and Region 2025-2033
出版日期: | 出版商: IMARC | 英文 137 Pages | 商品交期: 2-3個工作天內

價格

2024 年全球石油和天然氣人工智慧市場規模達 29 億美元。展望未來， IMARC Group預計到 2033 年市場規模將達到 64 億美元，2025-2033 年期間的成長率 (CAGR) 為 8.2%。石油和天然氣行業資料的爆炸性成長、對營運效率的需求不斷成長、對安全的日益重視、嚴格的環境法規的實施以及人工智慧 (AI) 演算法的最新技術進步是推動市場發展的一些主要因素。

石油天然氣領域的人工智慧是指人工智慧 (AI) 技術在石油天然氣產業最佳化流程、提高安全性和改善決策的應用。它包括神經網路、電腦視覺、機器學習 (ML)、機器人技術和自然語言處理 (NLP)。石油和天然氣領域的人工智慧廣泛應用於油藏模擬、自動化鑽井、預測性維護、地質測繪、安全監測、流程自動化和資產管理。它有助於決策、降低成本、提高安全性、改善可靠性、增強可擴展性和促進永續性。

人工智慧的廣泛應用為石油和天然氣行業提供了具有成本效益的解決方案，可以最佳化資源並簡化營運，從而推動市場成長。此外，嚴格的環境法規的實施迫使企業使用人工智慧來更好地遵守規定，並在石油和天然氣開採過程中盡量減少碳足跡，這對市場成長產生了積極的影響。此外，人工智慧演算法的最新技術進步，加上運算能力的提高，使得實施基於人工智慧的解決方案變得更加實用和高效，從而支持了市場的成長。除此之外，複雜任務技術人員的短缺日益加劇，也促進了對人工智慧的需求，以實現各種石油和天然氣鑽井作業的自動化能力。其他因素，包括對永續性的日益重視、對營運透明度的需求不斷增加以及石油和天然氣探勘的增加，預計將推動市場成長。

石油和天然氣市場人工智慧趨勢/促進因素：

石油和天然氣產業資料爆炸性成長

石油和天然氣產業正在產生來自感測器、鑽井設備和各種其他操作技術前所未有的資料量。與傳統的資料分析工具相比，人工智慧被廣泛用於即時有效地管理和解釋這些資料，這是有意義的。此外，它還提供高級分析功能，可以瀏覽大量資料集以檢查模式、趨勢和異常。除此之外，人工智慧還提供將原始資料轉化為有用見解的工具，可用於監控鑽井作業和最佳化供應鏈流程。此外，該公司正在增加對人工智慧解決方案的投資，以理解其資料並將其轉化為更明智決策的策略資產。

對營運效率的需求不斷成長

石油和天然氣行業涉及複雜且通常危險的操作，需要精心規劃和執行。此外，人為錯誤、設備故障或操作過程中任何部分的效率低下都可能導致重大的財務損失或安全風險。與此相符的是，人工智慧技術，特別是機器學習（ML）和預測分析，提供了顯著最佳化這些操作的能力。此外，它們還可以預測設備故障，自動執行重複性任務，並提高鑽井和開採過程的精確度。此外，人工智慧不僅可以降低成本，還可以最大限度地降低與人工錯誤和系統故障相關的風險。因此，營運效率是人工智慧融入石油和天然氣產業的主要促進因素。

越來越重視安全

由於石油和天然氣行業的作業（例如深海鑽探或使用高度易燃材料）具有危險性，因此越來越重視該行業的安全，從而推動了市場的成長。此外，傳統的安全措施往往無法完全消除事故和故障。與此相符，人工智慧透過即時監控、預測分析和自動控制系統提供了高級安全協定層。它可以分析來自多個感測器的資料，以檢測可能預示潛在事故的異常情況，從而能夠在事故發生之前採取預防措施。此外，人工智慧可以自動執行某些高風險任務，減少在潛在危險情況下人工干預的需要。因此，採用人工智慧技術來加強安全措施是推動市場成長的重要因素。

目錄

第1章：前言

第2章：範圍與方法

  • 研究目標
  • 利害關係人
  • 資料來源
    • 主要來源
    • 次要來源
  • 市場評估
    • 自下而上的方法
    • 自上而下的方法
  • 預測方法

第3章：執行摘要

第4章：簡介

  • 概述
  • 主要行業趨勢

第5章：全球石油和天然氣市場的人工智慧

  • 市場概覽
  • 市場表現
  • COVID-19的影響
  • 市場預測

第6章：市場細分：依類型

  • 硬體
  • 軟體
  • 服務

第7章：市場區隔：依功能

  • 預測性維護和機械檢查
  • 物質運動
  • 生產計劃
  • 現場服務
  • 品質管制
  • 開墾

第 8 章：市場區隔：按應用

  • 上游
  • 下游
  • 中游

第9章：市場細分：依地區

  • 北美洲
    • 美國
    • 加拿大
  • 亞太
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 其他
  • 歐洲
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 其他
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他
  • 中東和非洲
    • 市場區隔：依國家

第10章：SWOT分析

  • 概述
  • 優勢
  • 弱點
  • 機會
  • 威脅

第 11 章：價值鏈分析

第 12 章：波特五力分析

  • 概述
  • 買家的議價能力
  • 供應商的議價能力
  • 競爭程度
  • 新進入者的威脅
  • 替代品的威脅

第13章：價格分析

第 14 章：競爭格局

  • 市場結構
  • 關鍵參與者
  • 關鍵參與者簡介
    • Accenture plc
    • C3.AI Inc.
    • Cisco Systems Inc.
    • Cloudera Inc.
    • Fugenx Technologies
    • Huawei Technologies Co. Ltd
    • Infosys Limited
    • Intel Corporation
    • International Business Machines Corporation
    • Microsoft Corporation
    • Neudax
    • Nvidia Corporation
    • Oracle Corporation
    • Shell plc
Product Code: SR112025A6014

The global AI in oil and gas market size reached USD 2.9 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 6.4 Billion by 2033, exhibiting a growth rate (CAGR) of 8.2% during 2025-2033. The increasing data explosion in the oil and gas industry, rising demand for operational efficiency, growing emphasis on safety, imposition of strict environmental regulations, and the recent technological advancements in artificial intelligence (AI) algorithms are some of the major factors propelling the market.

AI in oil and gas refers to the application of artificial intelligence (AI) technologies in optimizing processes, enhancing safety, and improving decision-making in the oil and gas industry. It includes neural networks, computer visions, machine learning (ML), robotics, and natural language processing (NLP). AI in oil and gas is widely used in reservoir simulation, automated drilling, predictive maintenance, geological mapping, safety monitoring, process automation, and asset management. It aids in decision-making, reducing costs, increasing safety, improving reliability, enhancing scalability, and promoting sustainability.

The widespread adoption of AI to provide cost-effective solutions that can optimize resources and streamline operations across the oil and gas industry is propelling the market growth. Furthermore, the imposition of strict environmental regulations that are compelling firms to use AI for better compliance and to minimize their carbon footprint during oil and gas extraction is positively influencing the market growth. Additionally, the recent technological advancements in AI algorithms, coupled with increased computational power, which makes it more practical and efficient to implement AI-based solutions, are supporting the market growth. Besides this, the rising shortage of skilled personnel for complex tasks is facilitating the demand for AI to enable automation capabilities across various oil and gas drilling operations. Other factors, including the growing emphasis on sustainability, increasing demand for operational transparency, and rising oil and gas exploration, are anticipated to drive the market growth.

AI in Oil and Gas Market Trends/Drivers:

The increasing data explosion in the oil and gas industry

The oil and gas sector is generating an unprecedented volume of data stemming from sensors, drilling equipment, and various other operational technologies. As compared to traditional data analytics tools, AI is widely used to effectively manage and interpret this data in real-time, which is something. Furthermore, it offers advanced analytics capabilities that can browse through vast data sets to examine patterns, trends, and anomalies. Apart from this, AI provides the tools to transform raw data into useful insights that can be utilized for monitoring drilling operations and optimizing the supply chain processes. Moreover, companies are increasingly investing in AI solutions to make sense of their data and turn it into a strategic asset for smarter decision-making.

The rising demand for operational efficiency

The oil and gas sector involves complex, often hazardous operations that require meticulous planning and execution. Furthermore, human error, equipment failure, or inefficiencies in any part of the operation can result in significant financial losses or safety risks. In line with this, AI technologies, particularly machine learning (ML) and predictive analytics provide the capability to significantly optimize these operations. In addition, they can forecast equipment failures before they occur, automate repetitive tasks, and improve the precision of drilling and extraction processes. Moreover, AI not only reduces costs but also minimizes the risks associated with manual errors and system failures. As a result, operational efficiency is a major driving factor for the integration of AI in the oil and gas industry.

The growing emphasis on safety

The growing emphasis on safety in the oil and gas industry due to the hazardous nature of its operations, such as deep-sea drilling or working with highly flammable materials, is propelling the market growth. Furthermore, traditional safety measures often fall short of completely eliminating accidents and failures. In line with this, AI offers an advanced layer of safety protocols through real-time monitoring, predictive analytics, and automated control systems. It can analyze data from multiple sensors to detect irregularities that could signify a potential accident, enabling preventive actions to be taken before an incident occurs. Moreover, AI can automate certain high-risk tasks, reducing the need for manual intervention in potentially dangerous scenarios. As a result, the adoption of AI technologies for enhancing safety measures is a significant factor fueling the market growth.

AI in Oil and Gas Industry Segmentation:

Breakup by Type:

  • Hardware
  • Software
  • Services

Software dominate the market

Software is dominating the market as it offers excellent flexibility and scalability, which make it highly adaptable to diverse operational needs. Furthermore, it can be easily updated to include new algorithms or features, ensuring that the oil and gas operations remain at the forefront of technological advancements. In addition, software solutions are more cost-effective in the long term, as they eliminate the need for heavy machinery or additional hardware installations. Besides this, it can be seamlessly integrated into existing systems, allowing for the centralization of data and processes. This harmonization significantly improves data analytics, enabling more accurate and timely decision-making. Moreover, software can be deployed across multiple sites, providing a unified approach to operations management. Apart from this, it can be continuously refined to address specific issues and opportunities presented by the oil and gas sector.

Breakup by Function:

  • Predictive Maintenance and Machinery Inspection
  • Material Movement
  • Production Planning
  • Field Services
  • Quality Control
  • Reclamation

Predictive maintenance and machinery inspection hold the largest share in the market

Predictive maintenance and machinery inspection are dominating the market as they aid in reducing downtime by analyzing equipment data and predicting failures before they happen. Furthermore, they help in identifying wear and tear or other forms of degradation that, if not addressed, could lead to serious safety issues. By preemptively identifying potential problems, companies can replace or repair components as needed, thereby improving the overall safety of operations. Additionally, the advancement in sensor technology and the Internet of Things (IoT), which has made data collection more robust and accurate, making predictive maintenance and machinery inspection increasingly reliable and effective, is positively influencing the market growth. Moreover, predictive maintenance and machinery inspection offers a strong return on investment (ROI), as they reduce maintenance costs, increase operational efficiency, and enhance security protocols.

Breakup by Application:

  • Upstream
  • Downstream
  • Midstream

Upstream hold the largest share in the market

The upstream is dominating the market as it involves various complex and data-intensive tasks, such as drilling, exploration, and extraction of natural gas and crude oil. Furthermore, it requires extensive data analysis for geological interpretation and reservoir modeling to identify promising drilling locations. In addition, AI-based predictive analytics are widely used in upstream operations to forecast equipment failures, allowing for preemptive actions that can save both time and money. Besides this, AI-powered remote sensing technologies and robotics are widely utilized to perform critical tasks that are either hazardous for human workers or logistically challenging to manage, thereby enhancing safety and operational efficiency. Moreover, the widespread adoption of AI in the upstream sector due to the imposition of strict environmental regulations is favoring the market growth.

Breakup by Region:

  • North America
  • United States
  • Canada
  • Asia-Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others
  • Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • Russia
  • Others
  • Latin America
  • Brazil
  • Mexico
  • Others
  • Middle East and Africa

North America exhibits a clear dominance, accounting for the largest AI in oil and gas market share

The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.

North America has a well-developed infrastructure for both oil and gas extraction and AI technology, making it easier for companies to adopt and integrate AI solutions. Furthermore, the escalating level of investment in research and innovation by regional governments and private players to ensure continuous development and implementation of AI in the oil and gas sector is positively influencing the market growth. Besides this, companies in North America have a more mature understanding of the value of data analytics. This data-driven culture is conducive to the acceptance and optimization of AI capabilities across various sectors, including oil and gas. Moreover, the easy availability of a skilled workforce trained in data sciences and AI algorithms, which facilitates the implementation of advanced technologies, is contributing to the market growth.

Competitive Landscape:

Leading companies are leveraging machine learning (ML), predictive analytics, and natural language processing (NLP) to optimize every aspect of the oil and gas lifecycle, from exploration and drilling to production and distribution. Additionally, they are forging strategic partnerships with technology providers, academic institutions, and competitors to accelerate innovation and share knowledge. Furthermore, they are focusing on gaining customer insights to address specific problems and offer tailored solutions, which aids in building trust and improving overall customer satisfaction. Besides this, market leaders are investing in pilot programs to test the practical applications of AI technologies before full-scale implementation. Moreover, the escalating emphasis on sustainability and environmental responsibility has prompted companies to build AI solutions that meet the stringent regulatory requirements of various regions and countries.

The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

  • Accenture plc
  • C3.AI Inc.
  • Cisco Systems Inc.
  • Cloudera Inc.
  • Fugenx Technologies
  • Huawei Technologies Co. Ltd
  • Infosys Limited
  • Intel Corporation
  • International Business Machines Corporation
  • Microsoft Corporation
  • Neudax
  • Nvidia Corporation
  • Oracle Corporation
  • Shell plc.

Key Questions Answered in This Report

  • 1.What was the size of the global AI in oil and gas market in 2024?
  • 2.What is the expected growth rate of the global AI in oil and gas market during 2025-2033?
  • 3.What are the key factors driving the global AI in oil and gas market?
  • 4.What has been the impact of COVID-19 on the global AI in oil and gas market?
  • 5.What is the breakup of the global AI in oil and gas market based on the type?
  • 6.What is the breakup of the global AI in oil and gas market based on the function?
  • 7.What is the breakup of the global AI in oil and gas market based on the application?
  • 8.What are the key regions in the global AI in oil and gas market?
  • 9.Who are the key players/companies in the global AI in oil and gas market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global AI in Oil and Gas Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Forecast

6 Market Breakup by Type

  • 6.1 Hardware
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 Software
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast
  • 6.3 Services
    • 6.3.1 Market Trends
    • 6.3.2 Market Forecast

7 Market Breakup by Function

  • 7.1 Predictive Maintenance and Machinery Inspection
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Material Movement
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast
  • 7.3 Production Planning
    • 7.3.1 Market Trends
    • 7.3.2 Market Forecast
  • 7.4 Field Services
    • 7.4.1 Market Trends
    • 7.4.2 Market Forecast
  • 7.5 Quality Control
    • 7.5.1 Market Trends
    • 7.5.2 Market Forecast
  • 7.6 Reclamation
    • 7.6.1 Market Trends
    • 7.6.2 Market Forecast

8 Market Breakup by Application

  • 8.1 Upstream
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Downstream
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast
  • 8.3 Midstream
    • 8.3.1 Market Trends
    • 8.3.2 Market Forecast

9 Market Breakup by Region

  • 9.1 North America
    • 9.1.1 United States
      • 9.1.1.1 Market Trends
      • 9.1.1.2 Market Forecast
    • 9.1.2 Canada
      • 9.1.2.1 Market Trends
      • 9.1.2.2 Market Forecast
  • 9.2 Asia-Pacific
    • 9.2.1 China
      • 9.2.1.1 Market Trends
      • 9.2.1.2 Market Forecast
    • 9.2.2 Japan
      • 9.2.2.1 Market Trends
      • 9.2.2.2 Market Forecast
    • 9.2.3 India
      • 9.2.3.1 Market Trends
      • 9.2.3.2 Market Forecast
    • 9.2.4 South Korea
      • 9.2.4.1 Market Trends
      • 9.2.4.2 Market Forecast
    • 9.2.5 Australia
      • 9.2.5.1 Market Trends
      • 9.2.5.2 Market Forecast
    • 9.2.6 Indonesia
      • 9.2.6.1 Market Trends
      • 9.2.6.2 Market Forecast
    • 9.2.7 Others
      • 9.2.7.1 Market Trends
      • 9.2.7.2 Market Forecast
  • 9.3 Europe
    • 9.3.1 Germany
      • 9.3.1.1 Market Trends
      • 9.3.1.2 Market Forecast
    • 9.3.2 France
      • 9.3.2.1 Market Trends
      • 9.3.2.2 Market Forecast
    • 9.3.3 United Kingdom
      • 9.3.3.1 Market Trends
      • 9.3.3.2 Market Forecast
    • 9.3.4 Italy
      • 9.3.4.1 Market Trends
      • 9.3.4.2 Market Forecast
    • 9.3.5 Spain
      • 9.3.5.1 Market Trends
      • 9.3.5.2 Market Forecast
    • 9.3.6 Russia
      • 9.3.6.1 Market Trends
      • 9.3.6.2 Market Forecast
    • 9.3.7 Others
      • 9.3.7.1 Market Trends
      • 9.3.7.2 Market Forecast
  • 9.4 Latin America
    • 9.4.1 Brazil
      • 9.4.1.1 Market Trends
      • 9.4.1.2 Market Forecast
    • 9.4.2 Mexico
      • 9.4.2.1 Market Trends
      • 9.4.2.2 Market Forecast
    • 9.4.3 Others
      • 9.4.3.1 Market Trends
      • 9.4.3.2 Market Forecast
  • 9.5 Middle East and Africa
    • 9.5.1 Market Trends
    • 9.5.2 Market Breakup by Country
    • 9.5.3 Market Forecast

10 SWOT Analysis

  • 10.1 Overview
  • 10.2 Strengths
  • 10.3 Weaknesses
  • 10.4 Opportunities
  • 10.5 Threats

11 Value Chain Analysis

12 Porters Five Forces Analysis

  • 12.1 Overview
  • 12.2 Bargaining Power of Buyers
  • 12.3 Bargaining Power of Suppliers
  • 12.4 Degree of Competition
  • 12.5 Threat of New Entrants
  • 12.6 Threat of Substitutes

13 Price Analysis

14 Competitive Landscape

  • 14.1 Market Structure
  • 14.2 Key Players
  • 14.3 Profiles of Key Players
    • 14.3.1 Accenture plc
      • 14.3.1.1 Company Overview
      • 14.3.1.2 Product Portfolio
      • 14.3.1.3 Financials
      • 14.3.1.4 SWOT Analysis
    • 14.3.2 C3.AI Inc.
      • 14.3.2.1 Company Overview
      • 14.3.2.2 Product Portfolio
      • 14.3.2.3 Financials
    • 14.3.3 Cisco Systems Inc.
      • 14.3.3.1 Company Overview
      • 14.3.3.2 Product Portfolio
      • 14.3.3.3 Financials
      • 14.3.3.4 SWOT Analysis
    • 14.3.4 Cloudera Inc.
      • 14.3.4.1 Company Overview
      • 14.3.4.2 Product Portfolio
    • 14.3.5 Fugenx Technologies
      • 14.3.5.1 Company Overview
      • 14.3.5.2 Product Portfolio
    • 14.3.6 Huawei Technologies Co. Ltd
      • 14.3.6.1 Company Overview
      • 14.3.6.2 Product Portfolio
      • 14.3.6.3 SWOT Analysis
    • 14.3.7 Infosys Limited
      • 14.3.7.1 Company Overview
      • 14.3.7.2 Product Portfolio
      • 14.3.7.3 Financials
      • 14.3.7.4 SWOT Analysis
    • 14.3.8 Intel Corporation
      • 14.3.8.1 Company Overview
      • 14.3.8.2 Product Portfolio
      • 14.3.8.3 Financials
      • 14.3.8.4 SWOT Analysis
    • 14.3.9 International Business Machines Corporation
      • 14.3.9.1 Company Overview
      • 14.3.9.2 Product Portfolio
      • 14.3.9.3 Financials
    • 14.3.10 Microsoft Corporation
      • 14.3.10.1 Company Overview
      • 14.3.10.2 Product Portfolio
      • 14.3.10.3 Financials
      • 14.3.10.4 SWOT Analysis
    • 14.3.11 Neudax
      • 14.3.11.1 Company Overview
      • 14.3.11.2 Product Portfolio
    • 14.3.12 Nvidia Corporation
      • 14.3.12.1 Company Overview
      • 14.3.12.2 Product Portfolio
      • 14.3.12.3 Financials
      • 14.3.12.4 SWOT Analysis
    • 14.3.13 Oracle Corporation
      • 14.3.13.1 Company Overview
      • 14.3.13.2 Product Portfolio
      • 14.3.13.3 Financials
      • 14.3.13.4 SWOT Analysis
    • 14.3.14 Shell plc
      • 14.3.14.1 Company Overview
      • 14.3.14.2 Product Portfolio
      • 14.3.14.3 Financials

List of Figures

  • Figure 1: Global: AI in Oil and Gas Market: Major Drivers and Challenges
  • Figure 2: Global: AI in Oil and Gas Market: Sales Value (in Billion USD), 2019-2024
  • Figure 3: Global: AI in Oil and Gas Market Forecast: Sales Value (in Billion USD), 2025-2033
  • Figure 4: Global: AI in Oil and Gas Market: Breakup by Type (in %), 2024
  • Figure 5: Global: AI in Oil and Gas Market: Breakup by Function (in %), 2024
  • Figure 6: Global: AI in Oil and Gas Market: Breakup by Application (in %), 2024
  • Figure 7: Global: AI in Oil and Gas Market: Breakup by Region (in %), 2024
  • Figure 8: Global: AI in Oil and Gas (Hardware) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 9: Global: AI in Oil and Gas (Hardware) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 10: Global: AI in Oil and Gas (Software) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 11: Global: AI in Oil and Gas (Software) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 12: Global: AI in Oil and Gas (Services) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 13: Global: AI in Oil and Gas (Services) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 14: Global: AI in Oil and Gas (Predictive Maintenance and Machinery Inspection) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 15: Global: AI in Oil and Gas (Predictive Maintenance and Machinery Inspection) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 16: Global: AI in Oil and Gas (Material Movement) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 17: Global: AI in Oil and Gas (Material Movement) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 18: Global: AI in Oil and Gas (Production Planning) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 19: Global: AI in Oil and Gas (Production Planning) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 20: Global: AI in Oil and Gas (Field Services) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 21: Global: AI in Oil and Gas (Field Services) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 22: Global: AI in Oil and Gas (Quality Control) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 23: Global: AI in Oil and Gas (Quality Control) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 24: Global: AI in Oil and Gas (Reclamation) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 25: Global: AI in Oil and Gas (Reclamation) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 26: Global: AI in Oil and Gas (Upstream) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 27: Global: AI in Oil and Gas (Upstream) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 28: Global: AI in Oil and Gas (Downstream) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 29: Global: AI in Oil and Gas (Downstream) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 30: Global: AI in Oil and Gas (Midstream) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 31: Global: AI in Oil and Gas (Midstream) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 32: North America: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 33: North America: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 34: United States: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 35: United States: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 36: Canada: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 37: Canada: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 38: Asia-Pacific: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 39: Asia-Pacific: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 40: China: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 41: China: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 42: Japan: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 43: Japan: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 44: India: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 45: India: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 46: South Korea: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 47: South Korea: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 48: Australia: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 49: Australia: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 50: Indonesia: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 51: Indonesia: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 52: Others: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 53: Others: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 54: Europe: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 55: Europe: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 56: Germany: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 57: Germany: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 58: France: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 59: France: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 60: United Kingdom: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 61: United Kingdom: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 62: Italy: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 63: Italy: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 64: Spain: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 65: Spain: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 66: Russia: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 67: Russia: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 68: Others: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 69: Others: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 70: Latin America: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 71: Latin America: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 72: Brazil: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 73: Brazil: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 74: Mexico: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 75: Mexico: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 76: Others: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 77: Others: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 78: Middle East and Africa: AI in Oil and Gas Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 79: Middle East and Africa: AI in Oil and Gas Market: Breakup by Country (in %), 2024
  • Figure 80: Middle East and Africa: AI in Oil and Gas Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 81: Global: AI in Oil and Gas Industry: SWOT Analysis
  • Figure 82: Global: AI in Oil and Gas Industry: Value Chain Analysis
  • Figure 83: Global: AI in Oil and Gas Industry: Porter's Five Forces Analysis

List of Tables

  • Table 1: Global: AI in Oil and Gas Market: Key Industry Highlights, 2024 and 2033
  • Table 2: Global: AI in Oil and Gas Market Forecast: Breakup by Type (in Million USD), 2025-2033
  • Table 3: Global: AI in Oil and Gas Market Forecast: Breakup by Function (in Million USD), 2025-2033
  • Table 4: Global: AI in Oil and Gas Market Forecast: Breakup by Application (in Million USD), 2025-2033
  • Table 5: Global: AI in Oil and Gas Market Forecast: Breakup by Region (in Million USD), 2025-2033
  • Table 6: Global: AI in Oil and Gas Market: Competitive Structure
  • Table 7: Global: AI in Oil and Gas Market: Key Players