AI And ML In Oil And Gas Market Size 2025-2029
The ai and ml in oil and gas market size is forecast to increase by USD 5.9 billion, at a CAGR of 15.1% between 2024 and 2029.
The imperative for enhanced operational efficiency is a primary driver in the global AI and ML in oil and gas market, pushing companies to adopt technologies that optimize processes and reduce expenditures. Solutions incorporating generative ai in energy and machine learning (ML) market insights are being applied to everything from subsurface imaging to refinery process optimization. The emergence of generative AI and large language models for knowledge management represents a significant trend, enabling organizations to synthesize valuable insights from decades of unstructured data, such as drilling reports and maintenance logs. This shift toward advanced knowledge synthesis accelerates decision-making and de-risks new projects, fostering innovation across the sector.Despite these advancements, the industry's progress is moderated by pervasive data management and integration issues. Data is often trapped in technological and functional silos, stored in disparate systems with varied formats, which complicates the development of holistic AI models. The challenge lies in integrating structured numerical data with unstructured text and geospatial information to create a unified, analysis-ready foundation. This barrier of data fragmentation must be addressed to fully unlock the potential of technologies like applied ai in energy and utilities. Without a cohesive data strategy, even the most sophisticated algorithms, including those used for generative ai in automotive, will deliver suboptimal results, undermining confidence in these transformative tools.
What will be the Size of the AI And ML In Oil And Gas Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019 - 2023 and forecasts 2025-2029 - in the full report.
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The integration of AI and machine learning is dynamically reshaping operational paradigms across the oil and gas industry. Technologies such as seismic data interpretation and predictive drilling analytics are becoming central to upstream decision-making, enabling more precise reservoir characterization and well placement optimization. This evolution reflects a broader trend within the machine learning (ML) market toward specialized, high-impact applications. The focus is on translating vast datasets into actionable intelligence that mitigates exploration risks and enhances hydrocarbon recovery optimization.In midstream and downstream sectors, the application of digital twin technology and ai-powered drilling optimization systems is driving significant gains in asset integrity management and refinery process optimization. The push toward generative ai in energy is facilitating hyper-automation in midstream operations, where autonomous systems improve pipeline monitoring and logistical scheduling. This continuous deployment of intelligent systems underscores a strategic shift from reactive maintenance to proactive, predictive strategies aimed at reducing unplanned downtime and extending equipment lifespan across the entire value chain. The adoption of generative ai in automotive provides parallel insights into how these technologies scale.
How is this AI And ML In Oil And Gas Industry segmented?
The ai and ml in oil and gas industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019 - 2023 for the following segments.
- Component
- Application
- Predictive maintenance
- Production optimization
- Supply chain and logistics
- Exploration and drilling
- Others
- End-user
- Downstream
- Upstream
- Midstream
- Geography
- North America
- Europe
- APAC
- China
- India
- Japan
- South Korea
- Australia
- Middle East and Africa
- South America
- Rest of World (ROW)
By Component Insights
The solutions segment is estimated to witness significant growth during the forecast period.
Solutions represent the tangible technological core of the market, comprising the software, integrated platforms, and hardware that facilitate intelligent automation and data-driven decision-making. These offerings are moving beyond basic analytics to provide predictive and cognitive capabilities. The segment is broadly categorized into comprehensive platforms, which offer a unified environment for model development and deployment, and specialized point applications engineered to solve specific high-value problems. Europe represents 26.27% of the geographic opportunity, indicating substantial potential in the region.
These platforms often feature low-code interfaces designed to democratize AI, empowering domain experts like geoscientists to build models without extensive data science expertise. Specialized solutions include AI-powered software for seismic fault interpretation and predictive maintenance for critical equipment. A key trend is the integration of generative AI, which enables intuitive, conversational interfaces that lower the barrier to entry for leveraging complex data, accelerating insight generation across the enterprise and making solutions accessible to a broader range of personnel.
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The Solutions segment was valued at USD 3.0 billion in 2019 and showed a gradual increase during the forecast period.
Regional Analysis
APAC is estimated to contribute 29.6% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
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The APAC region constitutes a diverse and rapidly expanding market for AI and ML in oil and gas, shaped by a wide spectrum of participants. The primary drivers include the urgent need for greater energy security, the modernization of legacy infrastructure, and the strategic imperative for national oil companies (NOCS) to enhance operational efficiency. In Australia, a major LNG exporter, AI is used to optimize the liquefaction process and improve supply chain logistics. South America holds 3.96% of the global market opportunity.
For NOCs in countries like China and India, the focus is on leveraging AI to improve exploration success rates and maximize recovery from mature fields. A significant trend across Southeast Asia is the digital transformation of state-owned enterprises, which are partnering with global technology leaders to embed advanced analytics into their core processes. The region's vast downstream sector is also a fertile ground for AI adoption, with refineries deploying machine learning to optimize controls and manage complex supply chains for growing consumer markets.
Market Dynamics
Our researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
The global AI and ML in oil and gas market is witnessing transformative growth, driven by the imperative to enhance efficiency and safety in exploration and production. Companies are leveraging AI for subsurface reservoir modeling and employing deep learning for seismic data analysis to gain unprecedented geological insights. The effective unstructured data analysis in exploration is unlocking new reserve potential. For operational excellence, the focus is on autonomous systems for upstream operations and AI-powered drilling optimization systems, which are complemented by the real-time monitoring of drilling operations. Furthermore, machine learning for geosteering applications guides drilling with precision, while AI for wellbore integrity and safety mitigates operational risks. These technologies are crucial for maximizing returns from assets, especially in complex undertakings like AI for enhanced oil recovery projects.Across the value chain, the impact is profound, from optimizing production with machine learning to using a digital twin for asset performance. We see extensive AI applications in downstream refining and efforts toward optimizing LNG plant operational efficiency. Hyper-automation in midstream operations and advanced computer vision for pipeline leak detection enhance asset integrity, supported by machine learning for predictive maintenance. Technology enablers include edge computing for remote asset monitoring and the strategic use of generative AI for knowledge management. Firms are also deploying AI models for demand forecasting and achieving supply chain and logistics automation. Critically, these innovations are instrumental in managing ESG compliance with AI and reducing carbon footprint with AI, demonstrating the sector's commitment to a sustainable future.
What are the key market drivers leading to the rise in the adoption of AI And ML In Oil And Gas Industry?
- The critical need to improve operational efficiency and lower costs is a primary factor driving the adoption of AI and ML technologies in the oil and gas industry.
The relentless pursuit of operational efficiency and cost reduction remains a primary strategic driver. The adoption of artificial intelligence and machine learning offers transformative potential across the entire value chain, from upstream exploration to downstream distribution. In the upstream sector, ai for subsurface reservoir modeling is revolutionizing subsurface imaging and reservoir characterization. By processing vast quantities of seismic, geological, and production data, machine learning for predictive maintenance can generate more accurate 3d reservoir models. This capability significantly reduces exploration risks and optimizes well placement. In midstream and downstream operations, the focus is on asset integrity management and process control, where predictive maintenance is a cornerstone application. The Middle East and Africa represent 11.88% of the geographic opportunity, indicating significant potential.Intensifying pressure from investors, regulators, and the public to improve environmental performance, enhance operational safety, and adhere to stringent ESG criteria is a powerful driver for adoption. AI and ML offer sophisticated tools to address key ESG challenges, particularly in emissions reduction and safety management. A primary application is the monitoring and mitigation of greenhouse gas emissions, especially methane. AI-powered analytics, combined with data from satellites and drones, can identify and quantify emission sources with a high degree of accuracy. Beyond leak detection, AI is instrumental in optimizing operations for energy efficiency. On the safety front, computer vision for pipeline leak detection is transforming workplace monitoring by analyzing video feeds to automatically detect unsafe conditions, fostering a proactive safety culture.
What are the market trends shaping the AI And ML In Oil And Gas Industry?
- The rise of generative AI and large language models is a key trend transforming knowledge management by unlocking insights from vast unstructured data within the oil and gas sector.
A defining trend is the strategic application of generative ai and large language models to unlock value from unstructured data. Historically, the sector has struggled to analyze textual and qualitative data from sources like drilling reports, geological surveys, and maintenance logs. The advent of sophisticated llms, a key part of the generative ai in energy movement, is creating a paradigm shift from simple data retrieval to knowledge synthesis. This enables conversational interfaces where an engineer can pose a complex query in natural language and receive a coherent summary. The strategic implication is the democratization of specialized knowledge. This trend in the machine learning (ML) market empowers less experienced personnel to access organizational wisdom, improving operational consistency and safety. APAC is poised to contribute 29.6% of the market's incremental growth.The market is also witnessing a significant trend moving beyond discrete automation tasks towards hyper-automation, which integrates AI, machine learning, and RPA to create fully autonomous operational workflows. This represents an evolution from predictive to prescriptive, and ultimately, autonomous systems. The objective is the creation of self-optimizing assets, often referred to as the self-driving oilfield. In the upstream sector, this is materializing as neuro-autonomous drilling platforms that use real-time data to continuously adjust drilling parameters. Similarly, applied ai in energy and utilities is enabling autonomous inspection of pipelines and direct integration of AI optimization engines with refinery process control systems, achieving a level of efficiency beyond human cognitive capacity.
What challenges does the AI And ML In Oil And Gas Industry face during its growth?
- Widespread challenges related to data management and the integration of siloed information systems present a significant barrier to the effective deployment of AI and ML solutions.
A foundational challenge is the complex and fragmented nature of the data ecosystem. The industry generates immense volumes of data from disparate sources, but this data is frequently trapped in functional and technological silos. Subsurface geological data, real-time drilling data, and production sensor data are often stored in separate, proprietary systems not designed for interoperability. This creates a significant barrier to developing holistic AI models. The problem is exacerbated by the variety of data formats, from structured numerical data to unstructured text. Integrating these diverse types into a unified format is a monumental data engineering task. Furthermore, the quality and consistency of legacy data are often questionable, which can lead to unreliable AI model predictions. North America accounts for 28.3% of the geographic opportunity, highlighting its significant market presence.The adoption of advanced AI and ML solutions requires a substantial capital commitment, which is a considerable challenge in a capital-disciplined and cyclical industry. Costs extend beyond software to include high-performance computing infrastructure, analytics platforms, and cloud services for data storage. This high upfront investment is often met with skepticism from leadership, which traditionally evaluates projects based on clear, short-term return on investment metrics. The benefits of AI, such as improved operational efficiency or enhanced safety, can be difficult to quantify precisely beforehand. Many initiatives begin as pilot projects but struggle to scale due to a business case that is not compelling enough to justify the massive investment required, a phenomenon known as pilot purgatory.
Exclusive Customer Landscape
The ai and ml in oil and gas market forecasting report includes the adoption lifecycle of the market, covering from the innovator’s stage to the laggard’s stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the ai and ml in oil and gas market report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their market growth analysis strategies.
Customer Landscape
Key Companies & Market Insights
Companies are implementing various strategies, such as strategic alliances, ai and ml in oil and gas market forecast, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the industry.
ABB Ltd. - Offerings in this market provide advanced AI and ML capabilities through integrated platforms designed for real-time process optimization and emissions reduction. These solutions leverage machine learning to analyze operational data, delivering actionable insights that enhance efficiency and support environmental performance goals across industrial facilities.
The industry research and growth report includes detailed analyses of the competitive landscape of the market and information about key companies, including:
- ABB Ltd.
- Accenture PLC
- Baker Hughes Co.
- Beyond Limits
- BP Plc
- C3.ai Inc.
- Exxon Mobil Corp.
- Google LLC
- Halliburton Co.
- International Business Machines Corp.
- Microsoft Corp.
- Oracle Corp.
- Saudi Arabian Oil Co.
- Schlumberger Ltd.
- SensorUp Inc.
- Shell plc
- Siemens AG
- SparkCognition Inc.
- TechnipFMC plc
Qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key industry players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.
Recent Development and News in Ai And Ml In Oil And Gas Market
In April 2024, Microsoft and Cognite expanded their strategic partnership to integrate Microsoft Fabric with Cognite Data Fusion, aiming to simplify data analytics and enable generative AI capabilities for industrial customers, including those in the energy sector.In March 2024, C3 AI and AWS announced a deepened collaboration to offer the C3 Generative AI Suite on the AWS platform, focusing on accelerating enterprise adoption in key sectors such as energy and utilities.In February 2024, SLB announced significant enhancements to its Delfi digital platform, integrating new AI and ML-powered solutions for neuro-autonomous drilling designed to optimize drilling performance and efficiency in real-time.
Research Analyst Overview
The global AI and ML in oil and gas market is evolving as operators integrate advanced analytics into upstream activities. The application of machine learning for geophysics is refining processes such as seismic data interpretation and subsurface imaging, leading to more accurate subsurface geological modeling and reservoir characterization. This shift facilitates superior well placement optimization and real-time drilling optimization. Innovations in predictive drilling analytics and real-time geosteering are becoming standard, while the development of neuro-autonomous drilling continues to advance operational capabilities. Furthermore, AI models are enhancing complex recovery methods, including hydraulic fracturing design and steam-assisted gravity drainage, by optimizing drilling parameter optimization and enhanced oil recovery to maximize asset potential.Downstream and midstream sectors are adapting through the deployment of AI-driven systems for pipeline integrity management and refinery process optimization. The use of digital twin technology combined with the industrial internet of things provides a comprehensive view for asset integrity management and asset performance management. The integration of edge AI computing and cloud computing infrastructure supports real-time production monitoring and enables advanced demand forecasting models. The adoption of generative AI applications and large language models is beginning to reshape production workflow automation and SCADA systems analysis. Deployment of autonomous inspection drones and subsea inspection robotics improves safety, while robotic process automation streamlines operational technology integration. A focus on sustainability is also evident, with emissions quantification algorithms supporting methane emissions monitoring and carbon capture utilization. Industry analysis indicates an expected operational integration of AI technologies to increase by 14% across key segments.
Dive into Technavio’s robust research methodology, blending expert interviews, extensive data synthesis, and validated models for unparalleled AI And ML In Oil And Gas Market insights. See full methodology.
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Market Scope
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Report Coverage
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Details
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Page number
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281
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Base year
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2024
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Historic period
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2019 - 2023 |
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Forecast period
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2025-2029
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Growth momentum & CAGR
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Accelerating at a CAGR of 15.1%
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Market growth 2024-2029
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USD 5.9 billion
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Market structure
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Fragmented
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YoY growth 2024-2029(%)
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12.5%
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Key countries
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US, Canada, Russia, Germany, UK, France, China, India, Japan, South Korea, Australia, Saudi Arabia, UAE, Brazil, Argentina
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Competitive landscape
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Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks
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What are the Key Data Covered in this AI And ML In Oil And Gas Market Research and Growth Report?
- CAGR of the AI And ML In Oil And Gas industry during the forecast period
- Detailed information on factors that will drive the growth and forecasting between 2024 and 2029
- Precise estimation of the size of the market and its contribution of the industry in focus to the parent market
- Accurate predictions about upcoming growth and trends and changes in consumer behaviour
- Growth of the market across North America, Europe, APAC, Middle East and Africa, South America
- Thorough analysis of the market’s competitive landscape and detailed information about companies
- Comprehensive analysis of factors that will challenge the ai and ml in oil and gas market growth of industry companies
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1 Executive Summary
- 1 Executive Summary
- 1.1 Market overview
- Executive Summary - Chart on Market Overview
- Executive Summary - Data Table on Market Overview
- Executive Summary - Chart on Global Market Characteristics
- Executive Summary - Chart on Market by Geography
- Executive Summary - Chart on Market Segmentation by Component
- Executive Summary - Chart on Market Segmentation by Application
- Executive Summary - Chart on Market Segmentation by End-user
- Executive Summary - Chart on Incremental Growth
- Executive Summary - Data Table on Incremental Growth
- Executive Summary - Chart on Company Market Positioning
2 Technavio Analysis
- 2 Technavio Analysis
- 2.1 Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
- Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
- 2.2 Criticality of inputs and Factors of differentiation
- Chart on Overview on criticality of inputs and factors of differentiation
- 2.3 Factors of disruption
- Chart on Overview on factors of disruption
- 2.4 Impact of drivers and challenges
- Chart on Impact of drivers and challenges in 2024 and 2029
3 Market Landscape
- 3 Market Landscape
- 3.1 Market ecosystem
- Chart on Parent Market
- Data Table on - Parent Market
- 3.2 Market characteristics
- Chart on Market characteristics analysis
- 3.3 Value chain analysis
- Chart on Value chain analysis
4 Market Sizing
- 4 Market Sizing
- 4.1 Market definition
- Data Table on Offerings of companies included in the market definition
- 4.2 Market segment analysis
- 4.3 Market size 2024
- 4.4 Market outlook: Forecast for 2024-2029
- Chart on Global - Market size and forecast 2024-2029 ($ billion)
- Data Table on Global - Market size and forecast 2024-2029 ($ billion)
- Chart on Global Market: Year-over-year growth 2024-2029 (%)
- Data Table on Global Market: Year-over-year growth 2024-2029 (%)
5 Historic Market Size
- 5 Historic Market Size
- 5.1 Global AI And ML In Oil And Gas Market 2019 - 2023
- Historic Market Size - Data Table on Global AI And ML In Oil And Gas Market 2019 - 2023 ($ billion)
- 5.2 Component segment analysis 2019 - 2023
- Historic Market Size - Component Segment 2019 - 2023 ($ billion)
- 5.3 Application segment analysis 2019 - 2023
- Historic Market Size - Application Segment 2019 - 2023 ($ billion)
- 5.4 End-user segment analysis 2019 - 2023
- Historic Market Size - End-user Segment 2019 - 2023 ($ billion)
- 5.5 Geography segment analysis 2019 - 2023
- Historic Market Size - Geography Segment 2019 - 2023 ($ billion)
- 5.6 Country segment analysis 2019 - 2023
- Historic Market Size - Country Segment 2019 - 2023 ($ billion)
6 Five Forces Analysis
- 6 Five Forces Analysis
- 6.1 Five forces summary
- Five forces analysis - Comparison between 2024 and 2029
- 6.2 Bargaining power of buyers
- Bargaining power of buyers - Impact of key factors 2024 and 2029
- 6.3 Bargaining power of suppliers
- Bargaining power of suppliers - Impact of key factors in 2024 and 2029
- 6.4 Threat of new entrants
- Threat of new entrants - Impact of key factors in 2024 and 2029
- 6.5 Threat of substitutes
- Threat of substitutes - Impact of key factors in 2024 and 2029
- 6.6 Threat of rivalry
- Threat of rivalry - Impact of key factors in 2024 and 2029
- 6.7 Market condition
- Chart on Market condition - Five forces 2024 and 2029
7 Market Segmentation by Component
- 7 Market Segmentation by Component
- 7.1 Market segments
- Chart on Component - Market share 2024-2029 (%)
- Data Table on Component - Market share 2024-2029 (%)
- 7.2 Comparison by Component
- Chart on Comparison by Component
- Data Table on Comparison by Component
- 7.3 Solutions - Market size and forecast 2024-2029
- Chart on Solutions - Market size and forecast 2024-2029 ($ billion)
- Data Table on Solutions - Market size and forecast 2024-2029 ($ billion)
- Chart on Solutions - Year-over-year growth 2024-2029 (%)
- Data Table on Solutions - Year-over-year growth 2024-2029 (%)
- 7.4 Services - Market size and forecast 2024-2029
- Chart on Services - Market size and forecast 2024-2029 ($ billion)
- Data Table on Services - Market size and forecast 2024-2029 ($ billion)
- Chart on Services - Year-over-year growth 2024-2029 (%)
- Data Table on Services - Year-over-year growth 2024-2029 (%)
- 7.5 Market opportunity by Component
- Market opportunity by Component ($ billion)
- Data Table on Market opportunity by Component ($ billion)
8 Market Segmentation by Application
- 8 Market Segmentation by Application
- 8.1 Market segments
- Chart on Application - Market share 2024-2029 (%)
- Data Table on Application - Market share 2024-2029 (%)
- 8.2 Comparison by Application
- Chart on Comparison by Application
- Data Table on Comparison by Application
- 8.3 Predictive maintenance - Market size and forecast 2024-2029
- Chart on Predictive maintenance - Market size and forecast 2024-2029 ($ billion)
- Data Table on Predictive maintenance - Market size and forecast 2024-2029 ($ billion)
- Chart on Predictive maintenance - Year-over-year growth 2024-2029 (%)
- Data Table on Predictive maintenance - Year-over-year growth 2024-2029 (%)
- 8.4 Production optimization - Market size and forecast 2024-2029
- Chart on Production optimization - Market size and forecast 2024-2029 ($ billion)
- Data Table on Production optimization - Market size and forecast 2024-2029 ($ billion)
- Chart on Production optimization - Year-over-year growth 2024-2029 (%)
- Data Table on Production optimization - Year-over-year growth 2024-2029 (%)
- 8.5 Supply chain and logistics - Market size and forecast 2024-2029
- Chart on Supply chain and logistics - Market size and forecast 2024-2029 ($ billion)
- Data Table on Supply chain and logistics - Market size and forecast 2024-2029 ($ billion)
- Chart on Supply chain and logistics - Year-over-year growth 2024-2029 (%)
- Data Table on Supply chain and logistics - Year-over-year growth 2024-2029 (%)
- 8.6 Exploration and drilling - Market size and forecast 2024-2029
- Chart on Exploration and drilling - Market size and forecast 2024-2029 ($ billion)
- Data Table on Exploration and drilling - Market size and forecast 2024-2029 ($ billion)
- Chart on Exploration and drilling - Year-over-year growth 2024-2029 (%)
- Data Table on Exploration and drilling - Year-over-year growth 2024-2029 (%)
- 8.7 Others - Market size and forecast 2024-2029
- Chart on Others - Market size and forecast 2024-2029 ($ billion)
- Data Table on Others - Market size and forecast 2024-2029 ($ billion)
- Chart on Others - Year-over-year growth 2024-2029 (%)
- Data Table on Others - Year-over-year growth 2024-2029 (%)
- 8.8 Market opportunity by Application
- Market opportunity by Application ($ billion)
- Data Table on Market opportunity by Application ($ billion)
9 Market Segmentation by End-user
- 9 Market Segmentation by End-user
- 9.1 Market segments
- Chart on End-user - Market share 2024-2029 (%)
- Data Table on End-user - Market share 2024-2029 (%)
- 9.2 Comparison by End-user
- Chart on Comparison by End-user
- Data Table on Comparison by End-user
- 9.3 Downstream - Market size and forecast 2024-2029
- Chart on Downstream - Market size and forecast 2024-2029 ($ billion)
- Data Table on Downstream - Market size and forecast 2024-2029 ($ billion)
- Chart on Downstream - Year-over-year growth 2024-2029 (%)
- Data Table on Downstream - Year-over-year growth 2024-2029 (%)
- 9.4 Upstream - Market size and forecast 2024-2029
- Chart on Upstream - Market size and forecast 2024-2029 ($ billion)
- Data Table on Upstream - Market size and forecast 2024-2029 ($ billion)
- Chart on Upstream - Year-over-year growth 2024-2029 (%)
- Data Table on Upstream - Year-over-year growth 2024-2029 (%)
- 9.5 Midstream - Market size and forecast 2024-2029
- Chart on Midstream - Market size and forecast 2024-2029 ($ billion)
- Data Table on Midstream - Market size and forecast 2024-2029 ($ billion)
- Chart on Midstream - Year-over-year growth 2024-2029 (%)
- Data Table on Midstream - Year-over-year growth 2024-2029 (%)
- 9.6 Market opportunity by End-user
- Market opportunity by End-user ($ billion)
- Data Table on Market opportunity by End-user ($ billion)
10 Customer Landscape
- 10 Customer Landscape
- 10.1 Customer landscape overview
- Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
11 Geographic Landscape
- 11 Geographic Landscape
- 11.1 Geographic segmentation
- Chart on Market share by geography 2024-2029 (%)
- Data Table on Market share by geography 2024-2029 (%)
- 11.2 Geographic comparison
- Chart on Geographic comparison
- Data Table on Geographic comparison
- 11.3 North America - Market size and forecast 2024-2029
- Chart on North America - Market size and forecast 2024-2029 ($ billion)
- Data Table on North America - Market size and forecast 2024-2029 ($ billion)
- Chart on North America - Year-over-year growth 2024-2029 (%)
- Data Table on North America - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - North America
- Data Table on Regional Comparison - North America
- 11.3.1 US - Market size and forecast 2024-2029
- Chart on US - Market size and forecast 2024-2029 ($ billion)
- Data Table on US - Market size and forecast 2024-2029 ($ billion)
- Chart on US - Year-over-year growth 2024-2029 (%)
- Data Table on US - Year-over-year growth 2024-2029 (%)
- 11.3.2 Canada - Market size and forecast 2024-2029
- Chart on Canada - Market size and forecast 2024-2029 ($ billion)
- Data Table on Canada - Market size and forecast 2024-2029 ($ billion)
- Chart on Canada - Year-over-year growth 2024-2029 (%)
- Data Table on Canada - Year-over-year growth 2024-2029 (%)
- 11.4 Europe - Market size and forecast 2024-2029
- Chart on Europe - Market size and forecast 2024-2029 ($ billion)
- Data Table on Europe - Market size and forecast 2024-2029 ($ billion)
- Chart on Europe - Year-over-year growth 2024-2029 (%)
- Data Table on Europe - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - Europe
- Data Table on Regional Comparison - Europe
- 11.4.1 Russia - Market size and forecast 2024-2029
- Chart on Russia - Market size and forecast 2024-2029 ($ billion)
- Data Table on Russia - Market size and forecast 2024-2029 ($ billion)
- Chart on Russia - Year-over-year growth 2024-2029 (%)
- Data Table on Russia - Year-over-year growth 2024-2029 (%)
- 11.4.2 Germany - Market size and forecast 2024-2029
- Chart on Germany - Market size and forecast 2024-2029 ($ billion)
- Data Table on Germany - Market size and forecast 2024-2029 ($ billion)
- Chart on Germany - Year-over-year growth 2024-2029 (%)
- Data Table on Germany - Year-over-year growth 2024-2029 (%)
- 11.4.3 UK - Market size and forecast 2024-2029
- Chart on UK - Market size and forecast 2024-2029 ($ billion)
- Data Table on UK - Market size and forecast 2024-2029 ($ billion)
- Chart on UK - Year-over-year growth 2024-2029 (%)
- Data Table on UK - Year-over-year growth 2024-2029 (%)
- 11.4.4 France - Market size and forecast 2024-2029
- Chart on France - Market size and forecast 2024-2029 ($ billion)
- Data Table on France - Market size and forecast 2024-2029 ($ billion)
- Chart on France - Year-over-year growth 2024-2029 (%)
- Data Table on France - Year-over-year growth 2024-2029 (%)
- 11.5 APAC - Market size and forecast 2024-2029
- Chart on APAC - Market size and forecast 2024-2029 ($ billion)
- Data Table on APAC - Market size and forecast 2024-2029 ($ billion)
- Chart on APAC - Year-over-year growth 2024-2029 (%)
- Data Table on APAC - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - APAC
- Data Table on Regional Comparison - APAC
- 11.5.1 China - Market size and forecast 2024-2029
- Chart on China - Market size and forecast 2024-2029 ($ billion)
- Data Table on China - Market size and forecast 2024-2029 ($ billion)
- Chart on China - Year-over-year growth 2024-2029 (%)
- Data Table on China - Year-over-year growth 2024-2029 (%)
- 11.5.2 India - Market size and forecast 2024-2029
- Chart on India - Market size and forecast 2024-2029 ($ billion)
- Data Table on India - Market size and forecast 2024-2029 ($ billion)
- Chart on India - Year-over-year growth 2024-2029 (%)
- Data Table on India - Year-over-year growth 2024-2029 (%)
- 11.5.3 Japan - Market size and forecast 2024-2029
- Chart on Japan - Market size and forecast 2024-2029 ($ billion)
- Data Table on Japan - Market size and forecast 2024-2029 ($ billion)
- Chart on Japan - Year-over-year growth 2024-2029 (%)
- Data Table on Japan - Year-over-year growth 2024-2029 (%)
- 11.5.4 South Korea - Market size and forecast 2024-2029
- Chart on South Korea - Market size and forecast 2024-2029 ($ billion)
- Data Table on South Korea - Market size and forecast 2024-2029 ($ billion)
- Chart on South Korea - Year-over-year growth 2024-2029 (%)
- Data Table on South Korea - Year-over-year growth 2024-2029 (%)
- 11.5.5 Australia - Market size and forecast 2024-2029
- Chart on Australia - Market size and forecast 2024-2029 ($ billion)
- Data Table on Australia - Market size and forecast 2024-2029 ($ billion)
- Chart on Australia - Year-over-year growth 2024-2029 (%)
- Data Table on Australia - Year-over-year growth 2024-2029 (%)
- 11.6 Middle East and Africa - Market size and forecast 2024-2029
- Chart on Middle East and Africa - Market size and forecast 2024-2029 ($ billion)
- Data Table on Middle East and Africa - Market size and forecast 2024-2029 ($ billion)
- Chart on Middle East and Africa - Year-over-year growth 2024-2029 (%)
- Data Table on Middle East and Africa - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - Middle East and Africa
- Data Table on Regional Comparison - Middle East and Africa
- 11.6.1 Saudi Arabia - Market size and forecast 2024-2029
- Chart on Saudi Arabia - Market size and forecast 2024-2029 ($ billion)
- Data Table on Saudi Arabia - Market size and forecast 2024-2029 ($ billion)
- Chart on Saudi Arabia - Year-over-year growth 2024-2029 (%)
- Data Table on Saudi Arabia - Year-over-year growth 2024-2029 (%)
- 11.6.2 UAE - Market size and forecast 2024-2029
- Chart on UAE - Market size and forecast 2024-2029 ($ billion)
- Data Table on UAE - Market size and forecast 2024-2029 ($ billion)
- Chart on UAE - Year-over-year growth 2024-2029 (%)
- Data Table on UAE - Year-over-year growth 2024-2029 (%)
- 11.7 South America - Market size and forecast 2024-2029
- Chart on South America - Market size and forecast 2024-2029 ($ billion)
- Data Table on South America - Market size and forecast 2024-2029 ($ billion)
- Chart on South America - Year-over-year growth 2024-2029 (%)
- Data Table on South America - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - South America
- Data Table on Regional Comparison - South America
- 11.7.1 Brazil - Market size and forecast 2024-2029
- Chart on Brazil - Market size and forecast 2024-2029 ($ billion)
- Data Table on Brazil - Market size and forecast 2024-2029 ($ billion)
- Chart on Brazil - Year-over-year growth 2024-2029 (%)
- Data Table on Brazil - Year-over-year growth 2024-2029 (%)
- 11.7.2 Argentina - Market size and forecast 2024-2029
- Chart on Argentina - Market size and forecast 2024-2029 ($ billion)
- Data Table on Argentina - Market size and forecast 2024-2029 ($ billion)
- Chart on Argentina - Year-over-year growth 2024-2029 (%)
- Data Table on Argentina - Year-over-year growth 2024-2029 (%)
- 11.8 Market opportunity by geography
- Market opportunity by geography ($ billion)
- Data Tables on Market opportunity by geography ($ billion)
12 Drivers, Challenges, and Opportunity
- 12 Drivers, Challenges, and Opportunity
- 12.1 Market drivers
- Imperative for enhanced operational efficiency and cost reduction
- Escalating focus on environmental, social, and governance (ESG) compliance and safety
- Proliferation of big data and advancement of cloud computing infrastructure
- 12.2 Market challenges
- Pervasive data management and integration issues
- Significant upfront investment and ambiguous return on investment
- Critical talent shortage and organizational change management
- 12.3 Impact of drivers and challenges
- Impact of drivers and challenges in 2024 and 2029
- 12.4 Market opportunities
- Emergence of generative AI and large language models for knowledge management
- Hyper-automation and progression towards fully autonomous operations
- Proliferation of edge AI for real-time decision making in remote environments
13 Competitive Landscape
- 13 Competitive Landscape
- 13.1 Overview
- 13.2 Competitive Landscape
- Overview on criticality of inputs and factors of differentiation
- 13.3 Landscape disruption
- Overview on factors of disruption
- 13.4 Industry risks
- Impact of key risks on business
14 Competitive Analysis
- 14 Competitive Analysis
- 14.1 Companies profiled
- 14.2 Company ranking index
- 14.3 Market positioning of companies
- Matrix on companies position and classification
- 14.4 ABB Ltd.
- ABB Ltd. - Overview
- ABB Ltd. - Business segments
- ABB Ltd. - Key news
- ABB Ltd. - Key offerings
- ABB Ltd. - Segment focus
- SWOT
- 14.5 Accenture PLC
- Accenture PLC - Overview
- Accenture PLC - Business segments
- Accenture PLC - Key news
- Accenture PLC - Key offerings
- Accenture PLC - Segment focus
- SWOT
- 14.6 Baker Hughes Co.
- Baker Hughes Co. - Overview
- Baker Hughes Co. - Business segments
- Baker Hughes Co. - Key news
- Baker Hughes Co. - Key offerings
- Baker Hughes Co. - Segment focus
- SWOT
- 14.7 BP Plc
- BP Plc - Overview
- BP Plc - Business segments
- BP Plc - Key news
- BP Plc - Key offerings
- BP Plc - Segment focus
- SWOT
- 14.8 C3.ai Inc.
- C3.ai Inc. - Overview
- C3.ai Inc. - Product / Service
- C3.ai Inc. - Key news
- C3.ai Inc. - Key offerings
- SWOT
- 14.9 Exxon Mobil Corp.
- Exxon Mobil Corp. - Overview
- Exxon Mobil Corp. - Business segments
- Exxon Mobil Corp. - Key news
- Exxon Mobil Corp. - Key offerings
- Exxon Mobil Corp. - Segment focus
- SWOT
- 14.10 Google LLC
- Google LLC - Overview
- Google LLC - Product / Service
- Google LLC - Key offerings
- SWOT
- 14.11 Halliburton Co.
- Halliburton Co. - Overview
- Halliburton Co. - Business segments
- Halliburton Co. - Key news
- Halliburton Co. - Key offerings
- Halliburton Co. - Segment focus
- SWOT
- 14.12 International Business Machines Corp.
- International Business Machines Corp. - Overview
- International Business Machines Corp. - Business segments
- International Business Machines Corp. - Key news
- International Business Machines Corp. - Key offerings
- International Business Machines Corp. - Segment focus
- SWOT
- 14.13 Microsoft Corp.
- Microsoft Corp. - Overview
- Microsoft Corp. - Business segments
- Microsoft Corp. - Key news
- Microsoft Corp. - Key offerings
- Microsoft Corp. - Segment focus
- SWOT
- 14.14 Oracle Corp.
- Oracle Corp. - Overview
- Oracle Corp. - Business segments
- Oracle Corp. - Key news
- Oracle Corp. - Key offerings
- Oracle Corp. - Segment focus
- SWOT
- 14.15 Saudi Arabian Oil Co.
- Saudi Arabian Oil Co. - Overview
- Saudi Arabian Oil Co. - Product / Service
- Saudi Arabian Oil Co. - Key offerings
- SWOT
- 14.16 Schlumberger Ltd.
- Schlumberger Ltd. - Overview
- Schlumberger Ltd. - Business segments
- Schlumberger Ltd. - Key news
- Schlumberger Ltd. - Key offerings
- Schlumberger Ltd. - Segment focus
- SWOT
- 14.17 Shell plc
- Shell plc - Overview
- Shell plc - Business segments
- Shell plc - Key news
- Shell plc - Key offerings
- Shell plc - Segment focus
- SWOT
- 14.18 Siemens AG
- Siemens AG - Overview
- Siemens AG - Business segments
- Siemens AG - Key news
- Siemens AG - Key offerings
- Siemens AG - Segment focus
- SWOT
15 Appendix
- 15 Appendix
- 15.1 Scope of the report
- Market definition
- Objectives
- Notes and caveats
- 15.2 Inclusions and exclusions checklist
- Inclusions checklist
- Exclusions checklist
- 15.3 Currency conversion rates for US$
- Currency conversion rates for US$
- 15.4 Research methodology
- 15.5 Data procurement
- 15.6 Data validation
- 15.7 Validation techniques employed for market sizing
- Validation techniques employed for market sizing
- 15.8 Data synthesis
- 15.9 360 degree market analysis
- 360 degree market analysis
- 15.10 List of abbreviations
Research Framework
Technavio presents a detailed picture of the market by way of study, synthesis, and summation of data from multiple sources. The analysts have presented the various facets of the market with a particular focus on identifying the key industry influencers. The data thus presented is comprehensive, reliable, and the result of extensive research, both primary and secondary.
INFORMATION SOURCES
Primary sources
- Manufacturers and suppliers
- Channel partners
- Industry experts
- Strategic decision makers
Secondary sources
- Industry journals and periodicals
- Government data
- Financial reports of key industry players
- Historical data
- Press releases
DATA ANALYSIS
Data Synthesis
- Collation of data
- Estimation of key figures
- Analysis of derived insights
Data Validation
- Triangulation with data models
- Reference against proprietary databases
- Corroboration with industry experts
REPORT WRITING
Qualitative
- Market drivers
- Market challenges
- Market trends
- Five forces analysis
Quantitative
- Market size and forecast
- Market segmentation
- Geographical insights
- Competitive landscape
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