Artificial Intelligence systems spending market is forecast to reach a market size of USD 767.60 Billion by 2028, and register a significantly high CAGR, according to latest analysis by Emergen Research. Growth of the global Artificial Intelligence systems spending market in terms of revenue is expected to increase significantly during the forecast period due to rising demand for AI solutions in the education sector. Rising adoption of AI in the BFSI industry to provide enhanced customer service is also another major factor expected to further boost global Artificial Intelligence systems spending market growth during the forecast period. Rising focus of governments on digital economy transformation is expected to further support market growth going ahead.
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Competitive Landscape:
The latest study provides an insightful analysis of the broad competitive landscape of the global Artificial Intelligence Systems Spending market, emphasizing the key market rivals and their company profiles. A wide array of strategic initiatives, such as new business deals, mergers & acquisitions, collaborations, joint ventures, technological upgradation, and recent product launches, undertaken by these companies has been discussed in the report.
Key market participants include Google LLC, Microsoft Corporation, Apple Inc., Facebook, Inc., International Business Machines Corporation, Intel Corporation, Wipro Limited, Accenture PLC, Infosys Limited, and Salesforce.com Inc.
Key Points Covered in This Section:
The global Artificial Intelligence Systems Spending market report evaluates the latest economic scenario in terms of value and volume. It highlights the key growth drivers, restraints, production capacity, demand & supply ratio, import/export status, growth rate, and other critical aspects. Additionally, the report also performs SWOT analysis, Porter’s Five Forces analysis, speculation attainability investigation, and venture return investigation.
Emergen Research has segmented the global Artificial Intelligence systems spending market on the basis of component, technology, application, end-use, and region.
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Major Geographies Covered in the Report:
Table of Content
Chapter 1. Methodology & Sources
1.1. Market Definition
1.2. Research Scope
1.3. Methodology
1.4. Research Sources
1.4.1. Primary
1.4.2. Secondary
1.4.3. Paid Sources
1.5. Market Estimation Technique
Chapter 2. Executive Summary
2.1. Summary Snapshot, 2021-2028
Chapter 3. Key Insights
Chapter 4. Artificial Intelligence Systems Spending Market Segmentation & Impact Analysis
4.1. Artificial Intelligence Systems Spending Market Segmentation Analysis
4.2. Industrial Outlook
4.2.1. Market indicators analysis
4.2.2. Market drivers analysis
4.2.2.1. Increasing demand of artificial intelligence solutions in education sector
4.2.2.2. Growing implementation of artificial intelligence technology in pharmaceutical research and drug discovery.
4.2.2.3. Rising adoption of artificial intelligence in BFSI industry to provide enhanced customer service
4.2.2.4. Increasing adoption of artificial intelligence driven fraud detection systems in different industry
4.2.3. Market restraints analysis
4.2.3.1. High cost of artificial intelligence solutions
4.2.3.2. Concern of cyber attacks
4.3. Technological Insights
4.4. Regulatory Framework
4.5. Porter’s Five Forces Analysis
4.6. Competitive Metric Space Analysis
4.7. Price trend Analysis
4.8. Covid-19 Impact Analysis
Chapter 5. Artificial Intelligence Systems Spending Market By Component Insights & Trends Revenue (USD Billion)
5.1. Component Dynamics & Market Share, 2021 & 2028
5.1.1. Software
5.1.1.1. Applications
5.1.1.2. Platforms
5.1.2. Hardware
5.1.2.1. Server
5.1.2.2. Storage
5.1.3. Service
5.1.3.1. IT service
5.1.3.2. Business service
Chapter 6. Artificial Intelligence Systems Spending Market By Technology Insights & Trends Revenue (USD Billion)
6.1. Technology Dynamics & Market Share, 2021 & 2028
6.1.1. Natural language processing
6.1.2. Deep learning
6.1.3. Artificial general intelligence (AGI)
6.1.4. Machine vision
6.1.5. Artificial super intelligence (ASI)
6.1.6. Machine learning
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