The global AI in oil & gas market is anticipated to reach around US$2.9 Bn by 2030-end. Between the years of forecast, 2023 and 2030, the market is likely to display a staggering CAGR of 16.9%.
Market Analysis in Brief
Downtime is the nemesis of oil firms whose job is to turn barrels into money. Barrels might be lost during downtime, which results in lost revenue. The worst offenders are downtime that is not planned. When something goes wrong and there were no warning signs of concern, output may be unavailable for longer than anticipated. The health of the field and the producer's bottom line both depend on operations running well. Oil & gas companies must digitally empower themselves to be better prepared to respond quickly and boost business performance using novel strategies and concepts in the new (ab)normal environment. Artificial Intelligence (AI) value chain optimisation is crucial for this journey. The two most essential business goals for the oil & gas sector are to lower operating costs and increase levels of automation. AI helps with both goals.
Key Report Findings
- The global AI in oil & gas market sector will reach the valuation of US$2.9 Bn toward the end of 2030.
- In 2022, the predictive maintenance segment dominated the market with nearly 30.2% share, the upstream oil & gas sector recorded more than 51.8% market value share, and the services segment constituted more than 41.4% share of the market pie.
- North America held a notable market value share of more than 38% of the global AI in oil & gas market However, the Asia Pacific market for AI in oil & gas industry is expected to register the highest CAGR of 17.4%.
- The top five players steering the AI in oil & gas space include the top five players in the AI in oil & gas market include Google, IBM, Intel Corporation, Microsoft, and Oracle Corporation.
Market Drivers
Growing Need for Oil & Gas Value Chain Optimisation
In comparison to other industries, AI investments in the oil & gas industry account for 1-2% globally. Key oil & gas businesses utilising AI technologies include Shell, Exxon Mobil, BP, Chevron, Total, and Saudi Aramco. To prevent problems from occurring, oil & gas producers like Shell, and Oxy are now using AI in conjunction with a massive network of oil and gas sensors, and other machine learning tools. Drill operators can better comprehend the environment thanks to automated drilling systems that have been trained on data from simulations and data acquired by Shell, which speeds up results and lowers maintenance and expenses.
One-time Investment Costs with Improved RoI, and Increased Revenue
The influx of AI in the oil & gas industries is being driven by several factors, including an increase in productivity, lower downtime, Industry 4.0, sustainability goals, along with an increase in automated systems. O&G companies may completely reinvent how their businesses function and interact with their stakeholders by fusing AI with other exponential technologies. This could entail building engaging experiences for partners and employees, rethinking customer interaction, and establishing new ways to realise and monetise value.
Key barriers remain the data quality & seamless integration, investment cost. Investment in AI is essential because without it, organisations cannot achieve their most crucial business goals. The oil & gas industry has produced an average 32% RoI over the past year by utilising AI technologies. Over the past three years, a 3% expense reduction and 3% income gain were accomplished.
The COVID-19 pandemic posed enormous hurdles in front of the oil & gas sector. The industry's decline in demand coincided with production issues, which led to an oversupply of resources and the accompanying decline in oil prices. O&G companies are not unfamiliar with difficult external factors but they are now being compelled to change more quickly and agilely in order to meet the current situation and get ready for a new market reality.
While all of this is going on, O&G businesses are preparing for a bigger change that will move energy beyond hydrocarbons. To integrate sustainability goals, society, owners, and employees have higher expectations for operational integrity. They also anticipate more industry resilience in the face of potential future cyclical economic crises.
Upstream Sector to Register the Maximum Utilisation of AI Technologies
The global AI in oil & gas market has been segregated in terms of sector into upstream, midstream, and downstream. In 2022, upstream sector dominated the market and constituted more than 52% share.
Upstream AI aids in locating optimal well placements, enhancing drilling efficiency and safety, and enhancing oilfield performance in terms of recovery method and eventual recovery, or return on field. By keeping an eye on machinery, pumps, and compressors, AI in the midstream and downstream helps with regulating the process variables and lowering downtime related to the fractionating, purifying, and refining processes. AI helps estimate product flow, demand, and pricing with crude oil gathering to maximise profits.
AI Service Packages Secure the Top Spot
In terms of component, the global AI in oil & gas market has been segments into hardware, software, and services. The software segment has been further classified as deep learning, machine learning, and others.
In 2022, the services segment dominated and constituted 41.4% share by value. In the oil & gas industry, a portion of the technological budget is allocated to cloud computing, mobile, the Internet of Things, robotic process automation, and other technologies. In the following three years, it is anticipated that AI will account for the largest share of technology budgets, rising from 14% to 17%.
Service package is a combination of hardware and software which are procured as per the need and application. Companies offering these packages usually charge yearly as per the service contract with the oil & gas companies.
Predictive Maintenance Represents the Leading Market Segment
In terms of application, the global AI in oil & gas market has been classified as predictive maintenance, quality control, process optimisation, supply chain optimisation, physical security and cybersecurity, resource optimisation, data management, smart assistant, R&D, others. In 2022, the predictive maintenance segment constituted 30.2% share in 2022.
Advanced analytics, such as machine learning, are used in predictive maintenance to assess the state of a single asset or a group of assets (such as a factory). To obtain the most accurate reading possible, the most recent in predictive maintenance uses AI, and the Internet of Things (IoT). This enables a more proactive inspection strategy, detecting any issues and providing a fix.
Preventative maintenance has traditionally been the most effective technique to keep things running smoothly. i.e., scheduled downtime for the regular inspection of equipment for probable wear and tear and replacement. The problem with preventative maintenance is that it can occasionally be avoided. A review of equipment will find everything in order.
Growth Opportunities Across Regions
North America, and Asia Pacific Set to Reflect Strong Growth Potential Through 2030
Globally, the US is the largest end user of AI not only in oil & gas sector but throughout different sectors. North America is one of the leading players in the global AI in oil & gas. In 2022, the region accounted for around 38.2% of the global market for AI market for the oil & gas; throughout the forecast period, its share is anticipated to rise. In addition to being one of the biggest users of AI in oil & gas, North America is also a major global supplier of these services.
The American AI Initiative was introduced in 2019 by the US President Donald J. Trump as part of the country's plan to advance leadership in Artificial Intelligence. Federal authorities have promoted public trust in AI-based systems as part of this endeavour by defining standards for their creation and practical application across several industrial sectors.
The market of Asia Pacific is likely to witness strongest growth. By country, China is expected to lead the market. In 2023, researchers from China propose that the use of AI can enhance the safety and efficacy of fluidic catalytic cracking, a crucial process in converting heavy crude oil into gasoline and other products.
In the Middle East and Africa, AI in the oil & gas industry has a promising future. Aiming to advance AI, the governments of the UAE, Saudi Arabia, Qatar, and Egypt have unveiled comprehensive plans. Due to the COVID-19 pandemic, this was postponed. However, a research study released in March 2022 by the Saudi management consulting firm Strategic Gears advised the nation to concentrate on using AI to strengthen three industries - oil & gas, government services, and financial services - that already account for more than 50% of GDP.
Global AI in oil & gas market: Key Players
Some of the key players in global AI in oil & gas market include Google, IBM, SAS, Accenture Plc, Baidu, Inc., H2O.ai., Microsoft Corporation, Oracle Corporation, Siemens, Intel Corporation, and GE.
Notable Development
In 2021, ExxonMobil, a leader in the oil & gas industry for implementing digital technologies, worked with IBM's Data Science and AI Elite Team and seismic experts to apply AI to decipher and combine data from disparate systems into a single repository.
The Global AI in Oil & Gas Market is Segmented as Below-
By Application
- Predictive Maintenance
- Quality Control
- Process Optimization
- Supply Chain Optimization
- Physical & Cyber Security
- Resource Optimization
- Data Management
- Smart Assistant
- R&D
- Others
By Sector
- Upstream
- Midstream
- Downstream
By Component
- Hardware
- Software
- Deep Learning
- Machine Learning
- Others (computer vision, natural language processing, etc.)
- Services
By Region
- North America
- U.S.
- Canada
- Europe
- Germany
- Netherlands
- U.K.
- Italy
- Russia & CIS
- Rest of EU
- Asia Pacific
- China
- India
- Japan
- ASEAN
- Rest of Asia Pacific
- Middle East & Africa
- Iran
- Saudi Arabia
- UAE
- South Africa
- Rest of Middle East & Africa
- Latin America
- Brazil
- Mexico
- Venezuela
- Rest of Latin America
Key Players
- IBM
- SAS
- Accenture Plc
- Baidu, Inc.
- H2O.ai.
- Microsoft Corporation
- Oracle Corporation
- Siemens
- Intel Corporation
- GE
- Others
1. Executive Summary
1.1. Global AI Market in Oil & Gas Snapshot
1.2. Future Projections
1.3. Key Market Trends
1.4. Analyst Recommendations
2. Market Overview
2.1. Market Definitions and Segmentations
2.2. Market Dynamics
2.2.1. Drivers
2.2.2. Restraints
2.2.3. Market Opportunities
2.2.4. Economic Trends
2.3. Value Chain Analysis
2.4. Porter’s Five Forces Analysis
2.5. COVID-19 Impact
2.5.1. Supply Chain
2.5.2. End-user Industry Customer Impact Analysis
3. Price Trends Analysis, 2019 - 2030
4. Global AI Market in Oil & Gas Outlook, 2019 - 2030
4.1. Global AI Market in Oil & Gas Outlook, by Application, Value (US$ Mn), 2019 - 2030
4.1.1. Key Highlights
4.1.1.1. Predictive Maintenance
4.1.1.2. Quality Control
4.1.1.3. Process Optimization
4.1.1.4. Supply Chain Optimization
4.1.1.5. Physical & Cyber Security
4.1.1.6. Resource Optimization
4.1.1.7. Data Management
4.1.1.8. Smart Assistant
4.1.1.9. R&D
4.1.1.10. Others
4.1.2. BPS Analysis/Market Attractiveness Analysis, by Application
4.2. Global AI Market in Oil & Gas Outlook, by Sector, Value (US$ Mn), 2019 - 2030
4.2.1. Key Highlights
4.2.1.1. Upstream
4.2.1.2. Midstream
4.2.1.3. Downstream
4.2.2. BPS Analysis/Market Attractiveness Analysis, by Sector
4.3. Global AI Market in Oil & Gas Outlook, by Component, Value (US$ Mn), 2019 - 2030
4.3.1. Key Highlights
4.3.1.1. Hardware
4.3.1.2. Software
4.3.1.2.1. Deep Learning
4.3.1.2.2. Machine Learning
4.3.1.2.2. Others (computer vision, natural language processing, etc.)
4.3.1.3. Services
4.3.2. BPS Analysis/Market Attractiveness Analysis, by Component
4.4. Global AI Market in Oil & Gas Outlook, by Region, Value (US$ Mn), 2019 - 2030
4.4.1. Key Highlights
4.4.1.1. North America
4.4.1.2. Europe
4.4.1.3. Asia Pacific
4.4.1.4. Middle East & Africa
4.4.1.5. Latin America
4.4.2. BPS Analysis/Market Attractiveness Analysis, by Region
5. North America AI Market in Oil & Gas Outlook, 2019 - 2030
5.1. North America AI Market in Oil & Gas Outlook, by Application, Value (US$ Mn), 2019 - 2030
5.1.1. Key Highlights
5.1.1.1. Predictive Maintenance
5.1.1.2. Quality Control
5.1.1.3. Process Optimization
5.1.1.4. Supply Chain Optimization
5.1.1.5. Physical & Cyber Security
5.1.1.6. Resource Optimization
5.1.1.7. Data Management
5.1.1.8. Smart Assistant
5.1.1.9. R&D
5.1.1.10. Others
5.2. North America AI Market in Oil & Gas Outlook, by Sector, Value (US$ Mn), 2019 - 2030
5.2.1. Key Highlights
5.2.1.1. Upstream
5.2.1.2. Midstream
5.2.1.3. Downstream
5.3. North America AI Market in Oil & Gas Outlook, by Component, Value (US$ Mn), 2019 - 2030
5.3.1. Key Highlights
5.3.1.1. Hardware
5.3.1.2. Software
5.3.1.2.1. Deep Learning
5.3.1.2.2. Machine Learning
5.3.1.2.2. Others (computer vision, natural language processing, etc.)
5.3.1.3. Services
5.4. North America AI Market in Oil & Gas Outlook, by Country, Value (US$ Mn), 2019 - 2030
5.4.1. Key Highlights
5.4.1.1. U.S. AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
5.4.1.2. Canada AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
6. Europe AI Market in Oil & Gas Outlook, 2019 - 2030
6.1. Europe AI Market in Oil & Gas Outlook, by Application, Value (US$ Mn), 2019 - 2030
6.1.1. Key Highlights
6.1.1.1. Predictive Maintenance
6.1.1.2. Quality Control
6.1.1.3. Process Optimization
6.1.1.4. Supply Chain Optimization
6.1.1.5. Physical & Cyber Security
6.1.1.6. Resource Optimization
6.1.1.7. Data Management
6.1.1.8. Smart Assistant
6.1.1.9. R&D
6.1.1.10. Others
6.2. Europe AI Market in Oil & Gas Outlook, by Sector, Value (US$ Mn), 2019 - 2030
6.2.1. Key Highlights
6.2.1.1. Upstream
6.2.1.2. Midstream
6.2.1.3. Downstream
6.3. Europe AI Market in Oil & Gas Outlook, by Component, Value (US$ Mn), 2019 - 2030
6.3.1. Key Highlights
6.3.1.1. Hardware
6.3.1.2. Software
6.3.1.2.1. Deep Learning
6.3.1.2.2. Machine Learning
6.3.1.2.2. Others (computer vision, natural language processing, etc.)
6.3.1.3. Services
6.4. Europe AI Market in Oil & Gas Outlook, by Country, Value (US$ Mn), 2019 - 2030
6.4.1. Key Highlights
6.4.1.1. Germany AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
6.4.1.2. Netherland AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
6.4.1.3. U.K. AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
6.4.1.4. Italy AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
6.4.1.5. Russia & CIS AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
6.4.1.6. Rest of Europe AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
7. Asia Pacific AI Market in Oil & Gas Outlook, 2019 - 2030
7.1. Asia Pacific AI Market in Oil & Gas Outlook, by Application, Value (US$ Mn), 2019 - 2030
7.1.1. Key Highlights
7.1.1.1. Predictive Maintenance
7.1.1.2. Quality Control
7.1.1.3. Process Optimization
7.1.1.4. Supply Chain Optimization
7.1.1.5. Physical & Cyber Security
7.1.1.6. Resource Optimization
7.1.1.7. Data Management
7.1.1.8. Smart Assistant
7.1.1.9. R&D
7.1.1.10. Others
7.2. Asia Pacific AI Market in Oil & Gas Outlook, by Sector, Value (US$ Mn), 2019 - 2030
7.2.1. Key Highlights
7.2.1.1. Upstream
7.2.1.2. Midstream
7.2.1.3. Downstream
7.3. Asia Pacific AI Market in Oil & Gas Outlook, by Component, Value (US$ Mn), 2019 - 2030
7.3.1. Key Highlights
7.3.1.1. Hardware
7.3.1.2. Software
7.3.1.2.1. Deep Learning
7.3.1.2.2. Machine Learning
7.3.1.2.2. Others (computer vision, natural language processing, etc.)
7.3.1.3. Services
7.4. Asia Pacific AI Market in Oil & Gas Outlook, by Country, Value (US$ Mn), 2019 - 2030
7.4.1. Key Highlights
7.4.1.1. China AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
7.4.1.2. India AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
7.4.1.3. Japan AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
7.4.1.4. ASEAN AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
7.4.1.5. Rest of Asia Pacific AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
8. Middle East & Africa AI Market in Oil & Gas Outlook, 2019 - 2030
8.1. Middle East & Africa AI Market in Oil & Gas Outlook, by Application, Value (US$ Mn), 2019 - 2030
8.1.1. Key Highlights
8.1.1.1. Predictive Maintenance
8.1.1.2. Quality Control
8.1.1.3. Process Optimization
8.1.1.4. Supply Chain Optimization
8.1.1.5. Physical & Cyber Security
8.1.1.6. Resource Optimization
8.1.1.7. Data Management
8.1.1.8. Smart Assistant
8.1.1.9. R&D
8.1.1.10. Others
8.2. Middle East & Africa AI Market in Oil & Gas Outlook, by Sector, Value (US$ Mn), 2019 - 2030
8.2.1. Key Highlights
8.2.1.1. Upstream
8.2.1.2. Midstream
8.2.1.3. Downstream
8.3. Middle East & Africa AI Market in Oil & Gas Outlook, by Component, Value (US$ Mn), 2019 - 2030
8.3.1. Key Highlights
8.3.1.1. Hardware
8.3.1.2. Software
8.3.1.2.1. Deep Learning
8.3.1.2.2. Machine Learning
8.3.1.2.2. Others (computer vision, natural language processing, etc.)
8.3.1.3. Services
8.4. Middle East & Africa AI Market in Oil & Gas Outlook, by Country, Value (US$ Mn), 2019 - 2030
8.4.1. Key Highlights
8.4.1.1. Saudi Arabia AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
8.4.1.2. Iran AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
8.4.1.3. UAE AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
8.4.1.4. South Africa AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
8.4.1.5. Rest of Middle East & Africa AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
9. Latin America AI Market in Oil & Gas Outlook, 2019 - 2030
9.1. Latin America AI Market in Oil & Gas Outlook, by Application, Value (US$ Mn), 2019 - 2030
9.1.1. Key Highlights
9.1.1.1. Predictive Maintenance
9.1.1.2. Quality Control
9.1.1.3. Process Optimization
9.1.1.4. Supply Chain Optimization
9.1.1.5. Physical & Cyber Security
9.1.1.6. Resource Optimization
9.1.1.7. Data Management
9.1.1.8. Smart Assistant
9.1.1.9. R&D
9.1.1.10. Others
9.2. Latin America AI Market in Oil & Gas Outlook, by Sector, Value (US$ Mn), 2019 - 2030
9.2.1. Key Highlights
9.2.1.1. Upstream
9.2.1.2. Midstream
9.2.1.3. Downstream
9.3. Middle East & Africa AI Market in Oil & Gas Outlook, by Component, Value (US$ Mn), 2019 - 2030
9.3.1. Key Highlights
9.3.1.1. Hardware
9.3.1.2. Software
9.3.1.2.1. Deep Learning
9.3.1.2.2. Machine Learning
9.3.1.2.2. Others (computer vision, natural language processing, etc.)
9.3.1.3. Services
9.4. Latin America AI Market in Oil & Gas Outlook, by Country, Value (US$ Mn), 2019 - 2030
9.4.1. Key Highlights
9.4.1.1. Brazil AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, 2019 - 2030
9.4.1.2. Mexico AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, End-user Industry, 2019 - 2030
9.4.1.3. Venezuela AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, End-user Industry, 2019 - 2030
9.4.1.4. Rest of Latin America AI Market in Oil & Gas, Value (US$ Mn), by Application, Source, End-user Industry, 2019 - 2030
10. Competitive Landscape
10.1. Company Market Share Analysis, 2022
10.2. Strategic Collaborations
10.3. Company Profiles
10.3.1. Google
10.3.1.1. Company Overview
10.3.1.2. Product Portfolio
10.3.1.3. Financial Overview
10.3.1.4. Business Strategies and Development
10.3.2. IBM
10.3.2.1. Company Overview
10.3.2.2. Product Portfolio
10.3.2.3. Financial Overview
10.3.2.4. Business Strategies and Development
10.3.3. SAS
10.3.3.1. Company Overview
10.3.3.2. Product Portfolio
10.3.3.3. Financial Overview
10.3.3.4. Business Strategies and Development
10.3.4. Accenture
10.3.4.1. Company Overview
10.3.4.2. Product Portfolio
10.3.4.3. Financial Overview
10.3.4.4. Business Strategies and Development
10.3.5. Baidu, Inc.
10.3.5.1. Company Overview
10.3.5.2. Product Portfolio
10.3.5.3. Financial Overview
10.3.5.4. Business Strategies and Development
10.3.6. H2O.ai.
10.3.6.1. Company Overview
10.3.6.2. Product Portfolio
10.3.6.3. Financial Overview
10.3.6.4. Business Strategies and Development
10.3.7. Microsoft Corporation
10.3.7.1. Company Overview
10.3.7.2. Product Portfolio
10.3.7.3. Financial Overview
10.3.7.4. Business Strategies and Development
10.3.8. Oracle
10.3.8.1. Company Overview
10.3.8.2. Product Portfolio
10.3.8.3. Financial Overview
10.3.8.4. Business Strategies and Development
10.3.9. Siemens AG
10.3.9.1. Company Overview
10.3.9.2. Product Portfolio
10.3.9.3. Financial Overview
10.3.9.4. Business Strategies and Development
10.3.10. Intel Corporation
10.3.10.1. Company Overview
10.3.10.2. Product Portfolio
10.3.10.3. Financial Overview
10.3.10.4. Business Strategies and Development
10.3.11. GE & Others
10.3.11.1. Company Overview
10.3.11.2. Product Portfolio
10.3.11.3. Financial Overview
10.3.11.4. Business Strategies and Development
11. Appendix
11.1. Research Methodology
11.2. Report Assumptions
11.3. Acronyms and Abbreviations
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2022 |
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2019 - 2022 |
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2023 - 2030 |
Value: US$ Million |
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REPORT FEATURES |
DETAILS |
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Application Coverage |
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Sector Coverage |
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Component Coverage |
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Geographical Coverage |
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Leading Companies |
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Report Highlights |
Key Market Indicators, Macro-micro economic impact analysis, Technological Roadmap, Key Trends, Driver, Restraints, and Future Opportunities & Revenue Pockets, Porter’s 5 Forces Analysis, Historical Trend (2019-2021), Price Trend Analysis, Market Estimates and Forecast, Market Dynamics, Industry Trends, Competition Landscape, Category, Region, Country-wise Trends & Analysis, COVID-19 Impact Analysis (Demand and Supply Chain) |
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