Artificial Intelligence (AI) in Oil and Gas Market Introduction and Overview
According to SPER Market Research, the Global Artificial Intelligence (AI) in Oil and Gas Market is estimated to reach USD 7.53 billion by 2033 with a CAGR of 12.32%.
The report includes an in-depth analysis of the Global Artificial Intelligence (AI) in Oil and Gas market, including market size and trends, product mix, distribution channels, and supplier analysis. AI in the Oil and Gas business improves oil and gas output through predictive maintenance and machinery inspection, quality control, dwelling, exploration, tank and reservoir monitoring, and other measures, while also increasing profit in the oil and gas business. Machine learning, artificial neutral networks, fuzzy logic, and expert systems are examples of artificial intelligence tools that aid in the transformation of data into valuable information that can subsequently be utilized at various points of the lifecycle's exploration and production.
- In May 2023, Shell Plc announced a collaboration with SparkCognition, a big-data analytics company, to incorporate AI-driven technology into their deep-sea exploration and production efforts, aiming to enhance offshore oil production. Under this partnership, SparkCognition's AI algorithms will be employed to analyze a substantial volume of seismic data to assist Shell in identifying new oil reserves.
- In May 2023, UNIST, a South Korean national university, unveiled a significant alliance with ADNOC, the UAE's largest oil company, with the aim of spearheading the global digital carbon-neutral industry. This partnership is focused on pioneering the creation of an AI-powered decarbonization optimization system for large-scale oil refining and petrochemical operations.
Market Opportunities and Challenges
The rotary actuator market offers a number of opportunities, which are being driven by improvements in numerous sectors. The offshore oil and gas sectors harness artificial intelligence and data science to streamline the retrieval of intricate data necessary for their exploration and production activities. This facilitates the identification of fresh exploration prospects and enhances the utilization of existing infrastructure. As an illustration, BP plc reported that worldwide oil production reached 89.9 million barrels per day in 2021, and AI tools can play a pivotal role in boosting production.
Raw material price volatility is one of the reasons hampering the growth of the Artificial Intelligence (AI) in Oil and Gas market. Artificial Intelligence (AI) into the oil and gas sector comes with several obstacles. To begin, the industry grapples with vast quantities of data, and efficiently handling and analyzing this data remains a major challenge. Ensuring the precision, excellence, and reliability of data is vital for AI systems to produce dependable forecasts and choices. Furthermore, AI algorithms demand significant computational capacity, and numerous oil and gas facilities, particularly those situated in remote offshore areas, may lack the essential infrastructure to accommodate advanced AI applications. The process of integrating AI into existing systems can also be intricate and expensive.
Market Competitive Landscape
In January 2023, C3 AI, a company specializing in AI application software, unveiled the introduction of its C3 Generative AI Product Suite, marking the launch with its inaugural offering, C3 Generative AI for Enterprise Search. Within the C3 Generative AI Product Suite, C3 AI provides pre-developed AI applications that incorporate advanced transformer models, streamlining their utilization across various stages of the customer's operations. Furthermore, C3 Generative AI is poised to expedite transformation endeavors across diverse business functions and industries, including the oil and gas sector.
Scope of the Report:
| Report Metric | Details |
| Market size available for years | 2019-2033 |
| Base year considered | 2022 |
| Forecast period | 2023-2033 |
| Segments covered | By Component, By Operation
|
| Regions covered | North America, Asia-Pacific, Latin America, Middle East & Africa and Europe.
|
| Companies Covered | C3 AI, IBM, Flowserve Corporation, Google LLC, Microsoft Corporation, Oracle, FuGenX Technologies Pvt Ltd Inc, Cloudera Inc, Cisco Systems Inc, NVIDIA Corporation, Intel Corporation
|
COVID-19 Impact on Global Artificial Intelligence (AI) in Oil and Gas Market
The COVID-19 pandemic, there was a surge in global crude oil demand due to pent-up consumer demand. However, subsequent to this, macroeconomic challenges such as rising global interest rates and geopolitical tensions, notably the conflict in Ukraine, exerted pressure on crude oil prices once again.
Key Target Audience:
- Oil and Gas Companies
- AI Technology Providers
- Energy Investors
- Healthcare Industry
Our in-depth analysis of the Artificial Intelligence (AI) in Oil and Gas Market includes the following segments:
|
By Component:
|
Solution
Services
|
|
By Operation:
|
Upstream
Midstream
Downstream
|
Key Topics Covered in the Report:
- Global Artificial Intelligence (AI) in Oil and Gas Market Size (FY’2023-FY’2033)
- Overview of Global Artificial Intelligence (AI) in Oil and Gas Market
- Segmentation of Global Artificial Intelligence (AI) in Oil and Gas Market By Component (Solution, Services)
- Segmentation of Global Artificial Intelligence (AI) in Oil and Gas Market By Operation (Upstream, Midstream, Downstream)
- Statistical Snap of Global Artificial Intelligence (AI) in Oil and Gas Market
- Expansion Analysis of Global Artificial Intelligence (AI) in Oil and Gas Market
- Problems and Obstacles in Global Artificial Intelligence (AI) in Oil and Gas Market
- Competitive Landscape in the Global Artificial Intelligence (AI) in Oil and Gas Market
- Impact of COVID-19 and Demonetization on Global Artificial Intelligence (AI) in Oil and Gas Market
- Details on Current Investment in Global Artificial Intelligence (AI) in Oil and Gas Market
- Competitive Analysis of Global Artificial Intelligence (AI) in Oil and Gas Market
- Prominent Players in the Global Artificial Intelligence (AI) in Oil and Gas Market
- SWOT Analysis of Global Artificial Intelligence (AI) in Oil and Gas Market
- Global Artificial Intelligence (AI) in Oil and Gas Market Future Outlook and Projections (FY’2023-FY’2033)
- Recommendations from Analyst
1.Introduction
1.1.Scope of the report
1.2.Market segment analysis
2.Research Methodology
2.1.Research data source
2.1.1.Secondary Data
2.1.2.Primary Data
2.1.3.SPER’s internal database
2.1.4.Premium insight from KOL’s
2.2.Market size estimation
2.2.1.Top-down and Bottom-up approach
2.3.Data triangulation
3.Executive Summary
4.Market Dynamics
4.1.Driver, Restraint, Opportunity and Challenges analysis
4.1.1.Drivers
4.1.2.Restraints
4.1.3.Opportunities
4.1.4.Challenges
4.2.COVID-19 Impacts of the Global Artificial Intelligence (AI) in Oil and Gas Market
5.Market variable and outlook
5.1.SWOT Analysis
5.1.1.Strengths
5.1.2.Weaknesses
5.1.3.Opportunities
5.1.4.Threats
5.2.PESTEL Analysis
5.2.1.Political Landscape
5.2.2.Economic Landscape
5.2.3.Social Landscape
5.2.4.Technological Landscape
5.2.5.Environmental Landscape
5.2.6.Legal Landscape
5.3.PORTER’s Five Forces
5.3.1.Bargaining power of suppliers
5.3.2.Bargaining power of buyers
5.3.3.Threat of Substitute
5.3.4.Threat of new entrant
5.3.5.Competitive rivalry
5.4.Heat Map Analysis
6.Competitive Landscape
6.1.Global Artificial Intelligence (AI) in Oil and Gas Market Manufacturing Base Distribution, Sales Area, Product Type
6.2.Mergers & Acquisitions, Partnerships, Product Launch, and Collaboration in Global Artificial Intelligence (AI) in Oil and Gas Market
7.Global Artificial Intelligence (AI) in Oil and Gas Market, By Component (USD Million)
7.1.Global Artificial Intelligence (AI) in Oil and Gas Market Value Share and Forecast, By Component, 2023-2033
7.2.Solution
7.3.Services
8.Global Artificial Intelligence (AI) in Oil and Gas Market, By Operation (USD Million)
8.1.Global Artificial Intelligence (AI) in Oil and Gas Market Value Share and Forecast, By Operation, 2023-2033
8.2.Upstream
8.3.Midstream
8.4.Downstream
9.Global Artificial Intelligence (AI) in Oil and Gas Market Forecast, 2019-2033 (USD Million)
9.1.Global Artificial Intelligence (AI) in Oil and Gas Market Size and Market Share
10.Global Artificial Intelligence (AI) in Oil and Gas Market, By Component, 2019-2033 (USD Million)
10.1.Global Artificial Intelligence (AI) in Oil and Gas Market Size and Market Share By Component (2019-2026)
10.2.Global Artificial Intelligence (AI) in Oil and Gas Market Size and Market Share By Component (2027-2033)
11.Global Artificial Intelligence (AI) in Oil and Gas Market, By Operation, 2019-2033 (USD Million)
11.1.Global Artificial Intelligence (AI) in Oil and Gas Market Size and Market Share By Operation (2019-2026)
11.2.Global Artificial Intelligence (AI) in Oil and Gas Market Size and Market Share By Operation (2027-2033)
12.Global Artificial Intelligence (AI) in Oil and Gas Market, By Region, 2019-2033 (USD Million)
12.1.Global Artificial Intelligence (AI) in Oil and Gas Market Size and Market Share By Region (2019-2026)
12.2.Global Artificial Intelligence (AI) in Oil and Gas Market Size and Market Share By Region (2027-2033)
12.3.Asia-Pacific
12.3.1.Australia
12.3.2.China
12.3.3.India
12.3.4.Japan
12.3.5.South Korea
12.3.6.Rest of Asia-Pacific
12.4.Europe
12.4.1.France
12.4.2.Germany
12.4.3.Italy
12.4.4.Spain
12.4.5.United Kingdom
12.4.6.Rest of Europe
12.5.Middle East and Africa
12.5.1.Kingdom of Saudi Arabia
12.5.2.United Arab Emirates
12.5.3.Rest of Middle East & Africa
12.6.North America
12.6.1.Canada
12.6.2.Mexico
12.6.3.United States
12.7.Latin America
12.7.1.Argentina
12.7.2.Brazil
12.7.3.Rest of Latin America
13. Company Profile
13.1.C3.AI
13.1.1.Company details
13.1.2.Financial outlook
13.1.3.Product summary
13.1.4.Recent developments
13.2.IBM
13.2.1.Company details
13.2.2.Financial outlook
13.2.3.Product summary
13.2.4.Recent developments
13.3.Flowserve Corporation
13.3.1.Company details
13.3.2.Financial outlook
13.3.3.Product summary
13.3.4.Recent developments
13.4.Google LLC
13.4.1.Company details
13.4.2.Financial outlook
13.4.3.Product summary
13.4.4.Recent developments
13.5.Microsoft Corporation
13.5.1.Company details
13.5.2.Financial outlook
13.5.3.Product summary
13.5.4.Recent developments
13.6.Oracle
13.6.1.Company details
13.6.2.Financial outlook
13.6.3.Product summary
13.6.4.Recent development
13.7.FuGenX Technologies Pvt. Ltd. Inc
13.7.1.Company details
13.7.2.Financial outlook
13.7.3.Product summary
13.7.4.Recent development
13.8.Cloudera Inc
13.8.1.Company details
13.8.2.Financial outlook
13.8.3.Product summary
13.8.4.Recent development
13.9.Cisco Systems Inc
13.9.1.Company details
13.9.2.Financial outlook
13.9.3.Product summary
13.9.4.Recent development
13.10.NVIDIA Corporation
13.10.1.Company details
13.10.2.Financial outlook
13.10.3.Product summary
13.10.4.Recent development
13.11.Intel Corporation
13.11.1.Company details
13.11.2.Financial outlook
13.11.3.Product summary
13.11.4.Recent development
13.12.Others
14.List of Abbreviations
15.Reference Links
16.Conclusion
17.Research Scope
SPER Market Research’s methodology uses great emphasis on primary research to ensure that the market intelligence insights are up to date, reliable and accurate. Primary interviews are done with players involved in each phase of a supply chain to analyze the market forecasting. The secondary research method is used to help you fully understand how the future markets and the spending patterns look likes.
The report is based on in-depth qualitative and quantitative analysis of the Product Market. The quantitative analysis involves the application of various projection and sampling techniques. The qualitative analysis involves primary interviews, surveys, and vendor briefings. The data gathered as a result of these processes are validated through experts opinion. Our research methodology entails an ideal mixture of primary and secondary initiatives.
