AI 시장(-2035년) : 제공 구분별, 기술별, 전개별, 용도별, 최종사용자별, 지역별 산업 동향 및 예측

Artificial Intelligence Market Overview

As per Roots Analysis, the global artificial intelligence market size is estimated to grow from USD 273.6 billion in the current year to USD 5,267 billion by 2035, at a CAGR of 30.84% during the forecast period, till 2035.

The opportunity for artificial intelligence market has been distributed across the following segments:

Type of Offering

• Hardware
• Software
• Service

Type of Processing

• Cloud
• Edge

Type of Technology

• Computer Vision
• Context-Aware AI
• Experts Systems
• Machine Learning
• Natural Language Processing
• Robotics Process Automation

Type of Deployment

• Cloud-based
• On-Premises

Type of Application

• Automated Customer Service
• Fraud Detection & Risk Management
• Healthcare Diagnostics
• Marketing & Sales
• Predictive Analytics
• Robotics
• Supply Chain Optimization

Type of End User

• Automotive
• BFSI
• Energy & Utilities
• Government
• Healthcare
• Manufacturing
• Retail & E-Commerce
• Telecommunication

Geographical Regions

• North America
• US
• Canada
• Mexico
• Other North American countries
• Europe
• Austria
• Belgium
• Denmark
• France
• Germany
• Ireland
• Italy
• Netherlands
• Norway
• Russia
• Spain
• Sweden
• Switzerland
• UK
• Other European countries
• Asia
• China
• India
• Japan
• Singapore
• South Korea
• Other Asian countries
• Latin America
• Brazil
• Chile
• Colombia
• Venezuela
• Other Latin American countries
• Middle East and North Africa
• Egypt
• Iran
• Iraq
• Israel
• Kuwait
• Saudi Arabia
• UAE
• Other MENA countries
• Rest of the World
• Australia
• New Zealand
• Other countries

ARTIFICIAL INTELLIGENCE MARKET: GROWTH AND TRENDS

Artificial Intelligence (AI) refers to a wide area of computer science focused on developing machines that can execute tasks typically requiring human intelligence. This technology features various capabilities, including speaking, seeing, language comprehension and translation, and data analysis, marking it as one of the groundbreaking developments in the digital age. Additionally, it is worth mentioning that AI is a broad term that includes a variety of technologies, such as machine learning, deep learning, computer vision, and natural language processing.

As technology continues to evolve, AI is advancing quickly and is being widely adopted across almost all business sectors. Industries such as healthcare, finance, education, and manufacturing are utilizing this technology to enhance their data-driven processes and manage repetitive tasks, boosting the potential expansion of the global AI market. Throughout the years, the increasing implementation of industrial automation, the growing use of IoT devices, and ongoing technological progress have created new opportunities for industry participants. Consequently, stakeholders are making significant investments in AI research and development to address the evolving requirements of various sectors.

Driven by the rise of artificial general intelligence (AGI), the global artificial intelligence market is expected to grow at a healthy pace during the forecast period.

ARTIFICIAL INTELLIGENCE MARKET: KEY SEGMENTS

Market Share by Type of Offering

Based on the type of offering, the global artificial intelligence market is segmented into AI hardware, software, and service offerings. According to our estimates, currently, software segment captures the majority share of the market. This can be attributed to the wide range of applications, including natural language processing, computer vision, edge AI, machine learning, deep learning, and robotics, which are utilized across various sectors such as healthcare, automotive, and finance. However, cloud-based segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Technology

Based on the type of technology, the artificial intelligence market is segmented into computer vision, context-aware AI, experts systems, machine learning, natural language processing, and robotics process automation. According to our estimates, currently, machine learning segment captures the majority share of the market. This can be attributed to the fact that machine learning serves as a fundamental component of AI solutions, enabling the development of models that allow computers to learn from data, identify patterns, and make decisions. However, natural language processing segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Deployment

Based on the type of deployment, the artificial intelligence market is segmented into cloud-based and on-premises. According to our estimates, currently, cloud-based segment captures the majority share of the market; further, this segment is anticipated to grow at a higher CAGR in the future. This can be attributed to scalability and flexibility of cloud-based systems, allowing organizations to adjust AI resources based on their needs. Additionally, the cost-effectiveness of cloud-based options makes them increasingly popular and accessible to small and medium-sized enterprises with limited budgets, enabling them to take advantage of AI-as-a-service offerings at a manageable price.

Market Share by Type of Application

Based on the type of application, the artificial intelligence market is segmented into automated customer service, fraud detection & risk management, healthcare diagnostics, marketing & sales, predictive analytics, robotics, and supply chain optimization. According to our estimates, currently, marketing & sales segment captures the majority share of the market. This can be attributed to the prevalent use of AI technology for audience targeting and improving customer engagement. Additionally, companies are utilizing AI tools to enhance personalized marketing strategies and gain AI-driven customer insights and analytics. However, automated customer service segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of End User

Based on the type of end user, the artificial intelligence market is segmented into automotive, BFSI, energy & utilities, government, healthcare, manufacturing, retail & e-commerce, telecommunication, and others. According to our estimates, currently, BFSI segment captures the majority share of the market. This can be attributed to its increased use of AI technology to optimize operations, manage large volumes of financial data, detect fraud, and provide personalized customer experiences. However, healthcare segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Geographical Regions

Based on the geographical regions, the artificial intelligence market is segmented into North America, Europe, Asia, Latin America, Middle East and North Africa, and Rest of the World. According to our estimates, currently, North America captures the majority share of the market. However, market share in Asia is anticipated to grow at a higher CAGR during the forecast period.

Example Players in Artificial Intelligence Market

• Alibaba Cloud
• AMD
• Arrow AI
• AWS
• Baidu
• BMI
• Cisco
• DeepL
• Dilapad
• Glean
• Google
• HPE
• HQE System
• Huawei
• Inbenta
• Intel
• Meta
• Microsoft
• Moveworks
• NVIDIA
• OpenAI
• Oracle
• Qualcomm
• Salesforce
• SAP
• SAS Institute
• Siemens
• Spot AI

ARTIFICIAL INTELLIGENCE MARKET: RESEARCH COVERAGE

The report on the Artificial intelligence market features insights on various sections, including:

• Market Sizing and Opportunity Analysis: An in-depth analysis of the Artificial intelligence market, focusing on key market segments, including [A] type of offering, [B] type of technology, [C] type of deployment, [D] type of application, [E] type of end user and [F] geographical regions.
• Competitive Landscape: A comprehensive analysis of the companies engaged in the Artificial intelligence market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters, [D] ownership structure.
• Company Profiles: Elaborate profiles of prominent players engaged in the Artificial intelligence market, providing details on [A] location of headquarters, [B]company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] artificial intelligence portfolio, [J] moat analysis, [K] recent developments, and an informed future outlook.
• SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.

KEY QUESTIONS ANSWERED IN THIS REPORT

• How many companies are currently engaged in this market?
• Which are the leading companies in this market?
• What is the significance of edge AI in the Artificial intelligence market?
• What factors are likely to influence the evolution of this market?
• What is the current and future market size?
• What is the CAGR of this market?
• How is the current and future market opportunity likely to be distributed across key market segments?
• Which type of Artificial intelligence is expected to dominate the market?

REASONS TO BUY THIS REPORT

• The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
• Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
• The report offers stakeholders a comprehensive overview of the market, including key drivers, barriers, opportunities, and challenges. This information empowers stakeholders to stay abreast of market trends and make data-driven decisions to capitalize on growth prospects.

ADDITIONAL BENEFITS

• Complimentary Excel Data Packs for all Analytical Modules in the Report
• 10% Free Content Customization
• Detailed Report Walkthrough Session with Research Team
• Free Updated report if the report is 6-12 months old or older

TABLE OF CONTENTS

1. PREFACE

• 1.1. Introduction
• 1.2. Market Share Insights
• 1.3. Key Market Insights
• 1.4. Report Coverage
• 1.5. Key Questions Answered
• 1.6. Chapter Outlines

2. RESEARCH METHODOLOGY

• 2.1. Chapter Overview
• 2.2. Research Assumptions
• 2.3. Database Building
  • 2.3.1. Data Collection
  • 2.3.2. Data Validation
  • 2.3.3. Data Analysis
• 2.4. Project Methodology
  • 2.4.1. Secondary Research
    • 2.4.1.1. Annual Reports
    • 2.4.1.2. Academic Research Papers
    • 2.4.1.3. Company Websites
    • 2.4.1.4. Investor Presentations
    • 2.4.1.5. Regulatory Filings
    • 2.4.1.6. White Papers
    • 2.4.1.7. Industry Publications
    • 2.4.1.8. Conferences and Seminars
    • 2.4.1.9. Government Portals
    • 2.4.1.10. Media and Press Releases
    • 2.4.1.11. Newsletters
    • 2.4.1.12. Industry Databases
    • 2.4.1.13. Roots Proprietary Databases
    • 2.4.1.14. Paid Databases and Sources
    • 2.4.1.15. Social Media Portals
    • 2.4.1.16. Other Secondary Sources
  • 2.4.2. Primary Research
    • 2.4.2.1. Introduction
    • 2.4.2.2. Types
      • 2.4.2.2.1. Qualitative
      • 2.4.2.2.2. Quantitative
    • 2.4.2.3. Advantages
    • 2.4.2.4. Techniques
      • 2.4.2.4.1. Interviews
      • 2.4.2.4.2. Surveys
      • 2.4.2.4.3. Focus Groups
      • 2.4.2.4.4. Observational Research
      • 2.4.2.4.5. Social Media Interactions
    • 2.4.2.5. Stakeholders
      • 2.4.2.5.1. Company Executives (CXOs)
      • 2.4.2.5.2. Board of Directors
      • 2.4.2.5.3. Company Presidents and Vice Presidents
      • 2.4.2.5.4. Key Opinion Leaders
      • 2.4.2.5.5. Research and Development Heads
      • 2.4.2.5.6. Technical Experts
      • 2.4.2.5.7. Subject Matter Experts
      • 2.4.2.5.8. Scientists
      • 2.4.2.5.9. Doctors and Other Healthcare Providers
    • 2.4.2.6. Ethics and Integrity
      • 2.4.2.6.1. Research Ethics
      • 2.4.2.6.2. Data Integrity
  • 2.4.3. Analytical Tools and Databases

3. ECONOMIC AND OTHER PROJECT SPECIFIC CONSIDERATIONS

• 3.1. Forecast Methodology
  • 3.1.1. Top-Down Approach
  • 3.1.2. Bottom-Up Approach
  • 3.1.3. Hybrid Approach
• 3.2. Market Assessment Framework
  • 3.2.1. Total Addressable Market (TAM)
  • 3.2.2. Serviceable Addressable Market (SAM)
  • 3.2.3. Serviceable Obtainable Market (SOM)
  • 3.2.4. Currently Acquired Market (CAM)
• 3.3. Forecasting Tools and Techniques
  • 3.3.1. Qualitative Forecasting
  • 3.3.2. Correlation
  • 3.3.3. Regression
  • 3.3.4. Time Series Analysis
  • 3.3.5. Extrapolation
  • 3.3.6. Convergence
  • 3.3.7. Forecast Error Analysis
  • 3.3.8. Data Visualization
  • 3.3.9. Scenario Planning
  • 3.3.10. Sensitivity Analysis
• 3.4. Key Considerations
  • 3.4.1. Demographics
  • 3.4.2. Market Access
  • 3.4.3. Reimbursement Scenarios
  • 3.4.4. Industry Consolidation
• 3.5. Robust Quality Control
• 3.6. Key Market Segmentations
• 3.7. Limitations

4. MACRO-ECONOMIC INDICATORS

• 4.1. Chapter Overview
• 4.2. Market Dynamics
  • 4.2.1. Time Period
    • 4.2.1.1. Historical Trends
    • 4.2.1.2. Current and Forecasted Estimates
  • 4.2.2. Currency Coverage
    • 4.2.2.1. Overview of Major Currencies Affecting the Market
    • 4.2.2.2. Impact of Currency Fluctuations on the Industry
  • 4.2.3. Foreign Exchange Impact
    • 4.2.3.1. Evaluation of Foreign Exchange Rates and Their Impact on Market
    • 4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
  • 4.2.4. Recession
    • 4.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
    • 4.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
  • 4.2.5. Inflation
    • 4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
    • 4.2.5.2. Potential Impact of Inflation on the Market Evolution
  • 4.2.6. Interest Rates
    • 4.2.6.1. Overview of Interest Rates and Their Impact on the Market
    • 4.2.6.2. Strategies for Managing Interest Rate Risk
  • 4.2.7. Commodity Flow Analysis
    • 4.2.7.1. Type of Commodity
    • 4.2.7.2. Origins and Destinations
    • 4.2.7.3. Values and Weights
    • 4.2.7.4. Modes of Transportation
  • 4.2.8. Global Trade Dynamics
    • 4.2.8.1. Import Scenario
    • 4.2.8.2. Export Scenario
  • 4.2.9. War Impact Analysis
    • 4.2.9.1. Russian-Ukraine War
    • 4.2.9.2. Israel-Hamas War
  • 4.2.10. COVID Impact / Related Factors
    • 4.2.10.1. Global Economic Impact
    • 4.2.10.2. Industry-specific Impact
    • 4.2.10.3. Government Response and Stimulus Measures
    • 4.2.10.4. Future Outlook and Adaptation Strategies
  • 4.2.11. Other Indicators
    • 4.2.11.1. Fiscal Policy
    • 4.2.11.2. Consumer Spending
    • 4.2.11.3. Gross Domestic Product (GDP)
    • 4.2.11.4. Employment
    • 4.2.11.5. Taxes
    • 4.2.11.6. R&D Innovation
    • 4.2.11.7. Stock Market Performance
    • 4.2.11.8. Supply Chain
    • 4.2.11.9. Cross-Border Dynamics

5. EXECUTIVE SUMMARY

6. INTRODUCTION

• 6.1. Chapter Overview
• 6.2. Overview of Artificial Intelligence Market
  • 6.2.1. Type of Offering
  • 6.2.2. Type of Technology
  • 6.2.3. Type of Deployment
  • 6.2.4. Type of Application
  • 6.2.5. Type of End User
• 6.3. Future Perspective

7. COMPETITIVE LANDSCAPE

• 7.1. Chapter Overview
• 7.2. Artificial Intelligence: Overall Market Landscape
  • 7.2.1. Analysis by Year of Establishment
  • 7.2.2. Analysis by Company Size
  • 7.2.3. Analysis by Location of Headquarters
  • 7.2.4. Analysis by Ownership Structure

8. COMPANY PROFILES

• 8.1. Chapter Overview
• 8.2. Alibaba Cloud*
  • 8.2.1. Company Overview
  • 8.2.2. Company Mission
  • 8.2.3. Company Footprint
  • 8.2.4. Management Team
  • 8.2.5. Contact Details
  • 8.2.6. Financial Performance
  • 8.2.7. Operating Business Segments
  • 8.2.8. Service / Product Portfolio (project specific)
  • 8.2.9. MOAT Analysis
  • 8.2.10. Recent Developments and Future Outlook
• 8.3. AMD
• 8.4. AMD
• 8.5. Arrow AI
• 8.6. AWS
• 8.7. Baidu
• 8.8. BMI
• 8.9. Cisco
• 8.10. DeepL
• 8.11. Dialpad
• 8.12. Glean
• 8.13. Google
• 8.14. Golden Omega
• 8.15. HPE
• 8.16. HQE System
• 8.17. Koninklijke
• 8.18. Huawei
• 8.19. Inbenta
• 8.20. Intel
• 8.21. Meta
• 8.22. Microsoft
• 8.23. Moveworks
• 8.24. NVIDIA
• 8.25. OpenAI
• 8.26. Oracle
• 8.27. Qualcomm
• 8.28. Salesforce
• 8.29. SAP
• 8.30. Seimens

9. VALUE CHAIN ANALYSIS

10. SWOT ANALYSIS

11. GLOBAL ARTIFICIAL INTELLIGENCE MARKET

• 11.1. Chapter Overview
• 11.2. Key Assumptions and Methodology
• 11.3. Trends Disruption Impacting Market
• 11.4. Global Artificial Intelligence Market, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 11.5. Multivariate Scenario Analysis
  • 11.5.1. Conservative Scenario
  • 11.5.2. Optimistic Scenario
• 11.6. Key Market Segmentations

12. MARKET OPPORTUNITIES BASED ON TYPE OF OFFERING

• 12.1. Chapter Overview
• 12.2. Key Assumptions and Methodology
• 12.3. Revenue Shift Analysis
• 12.4. Market Movement Analysis
• 12.5. Penetration-Growth (P-G) Matrix
• 12.6. Artificial Intelligence Market for Hardware: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 12.7. Artificial Intelligence Market for Software: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 12.8. Artificial Intelligence Market for Services: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 12.9. Data Triangulation and Validation

13. MARKET OPPORTUNITIES BASED ON TYPE OF TECHNOLOGY

• 13.1. Chapter Overview
• 13.2. Key Assumptions and Methodology
• 13.3. Revenue Shift Analysis
• 13.4. Market Movement Analysis
• 13.5. Penetration-Growth (P-G) Matrix
• 13.6. Artificial Intelligence Market for Computer Vision: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 13.7. Artificial Intelligence Market for Context-Aware AI: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 13.8. Artificial Intelligence Market for Experts Systems: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 13.9. Artificial Intelligence Market for Machine Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 13.10. Artificial Intelligence Market for Natural Language Processing: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 13.11. Artificial Intelligence Market for Robotics Process Automation: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 13.12. Data Triangulation and Validation

14. MARKET OPPORTUNITIES BASED ON TYPE OF DEPLOYMENT

• 14.1 Chapter Overview
• 14.2 Key Assumptions and Methodology
• 14.3. Revenue Shift Analysis
• 14.4. Market Movement Analysis
• 14.5. Penetration-Growth (P-G) Matrix
• 14.6. Artificial Intelligence Market for Cloud-Based: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 14.7. Artificial Intelligence Market for On-Premises: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 14.8. Data Triangulation and Validation

15. MARKET OPPORTUNITIES BASED ON TYPE OF APPLICATION

• 15.1 Chapter Overview
• 15.2 Key Assumptions and Methodology
• 15.3. Revenue Shift Analysis
• 15.4. Market Movement Analysis
• 15.5. Penetration-Growth (P-G) Matrix
• 15.6. Artificial Intelligence Market for Automated Customer Service: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 15.7. Artificial Intelligence Market for Fraud Detection & Risk Management: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 15.8. Artificial Intelligence Market for Healthcare Diagnostics: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 15.9. Artificial Intelligence Market for Marketing & Sales: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 15.10. Artificial Intelligence Market for Predictive Analytics: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 15.11. Artificial Intelligence Market for Robotics: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 15.12. Artificial Intelligence Market for Supply Chain Optimization: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 15.13. Data Triangulation and Validation

16. MARKET OPPORTUNITIES BASED ON TYPE OF END USER

• 16.1. Chapter Overview
• 16.2. Key Assumptions and Methodology
• 16.3. Revenue Shift Analysis
• 16.4. Market Movement Analysis
• 16.5. Penetration-Growth (P-G) Matrix
• 16.6. Artificial Intelligence Market for Automotive: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.7. Artificial Intelligence Market for BFSI: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.8. Artificial Intelligence Market for Energy & Utilities: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.9. Artificial Intelligence Market for Government: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.10. Artificial Intelligence Market for Healthcare: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.11. Artificial Intelligence Market for Manufacturing: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.12. Artificial Intelligence Market for Retail & E-Commerce: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.13. Artificial Intelligence Market for Telecommunication: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.14. Artificial Intelligence Market for Others: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 16.15. Data Triangulation and Validation

17. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN NORTH AMERICA

• 17.1. Chapter Overview
• 17.2. Key Assumptions and Methodology
• 17.3. Revenue Shift Analysis
• 17.4. Market Movement Analysis
• 17.5. Penetration-Growth (P-G) Matrix
• 17.6. Artificial Intelligence Market in North America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 17.6.1. Artificial Intelligence Market in the US: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 17.6.2. Artificial Intelligence Market in Canada: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 17.6.3. Artificial Intelligence Market in Mexico: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 17.6.4. Artificial Intelligence Market in Other North American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 17.7. Data Triangulation and Validation

18. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN EUROPE

• 18.1. Chapter Overview
• 18.2. Key Assumptions and Methodology
• 18.3. Revenue Shift Analysis
• 18.4. Market Movement Analysis
• 18.5. Penetration-Growth (P-G) Matrix
• 18.6. Artificial Intelligence Market in Europe: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.1. Artificial Intelligence Market in Austria: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.2. Artificial Intelligence Market in Belgium: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.3. Artificial Intelligence Market in Denmark: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.4. Artificial Intelligence Market in France: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.5. Artificial Intelligence Market in Germany: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.6. Artificial Intelligence Market in Ireland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.7. Artificial Intelligence Market in Italy: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.8. Artificial Intelligence Market in Netherlands: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.9. Artificial Intelligence Market in Norway: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.10. Artificial Intelligence Market in Russia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.11. Artificial Intelligence Market in Spain: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.12. Artificial Intelligence Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.13. Artificial Intelligence Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.14. Artificial Intelligence Market in Switzerland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.15. Artificial Intelligence Market in the UK: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.6.16. Artificial Intelligence Marketing Other European Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 18.7. Data Triangulation and Validation

19. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN ASIA

• 19.1. Chapter Overview
• 19.2. Key Assumptions and Methodology
• 19.3. Revenue Shift Analysis
• 19.4. Market Movement Analysis
• 19.5. Penetration-Growth (P-G) Matrix
• 19.6. Artificial Intelligence Market in Asia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.6.1. Artificial Intelligence Market in China: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.6.2. Artificial Intelligence Market in India: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.6.3. Artificial Intelligence Market in Japan: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.6.4. Artificial Intelligence Market in Singapore: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.6.5. Artificial Intelligence Market in South Korea: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.6.6. Artificial Intelligence Market in Other Asian Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 19.7. Data Triangulation and Validation

20. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN MIDDLE EAST AND NORTH AFRICA (MENA)

• 20.1. Chapter Overview
• 20.2. Key Assumptions and Methodology
• 20.3. Revenue Shift Analysis
• 20.4. Market Movement Analysis
• 20.5. Penetration-Growth (P-G) Matrix
• 20.6. Artificial Intelligence Market in Middle East and North Africa (MENA): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.6.1. Artificial Intelligence Market in Egypt: Historical Trends (Since 2019) and Forecasted Estimates (Till 205)
  • 20.6.2. Artificial Intelligence Market in Iran: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.6.3. Artificial Intelligence Market in Iraq: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.6.4. Artificial Intelligence Market in Israel: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.6.5. Artificial Intelligence Market in Kuwait: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.6.6. Artificial Intelligence Market in Saudi Arabia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.6.7. Artificial Intelligence Market in United Arab Emirates (UAE): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.6.8. Artificial Intelligence Market in Other MENA Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 20.7. Data Triangulation and Validation

21. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN LATIN AMERICA

• 21.1. Chapter Overview
• 21.2. Key Assumptions and Methodology
• 21.3. Revenue Shift Analysis
• 21.4. Market Movement Analysis
• 21.5. Penetration-Growth (P-G) Matrix
• 21.6. Artificial Intelligence Market in Latin America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.6.1. Artificial Intelligence Market in Argentina: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.6.2. Artificial Intelligence Market in Brazil: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.6.3. Artificial Intelligence Market in Chile: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.6.4. Artificial Intelligence Market in Colombia Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.6.5. Artificial Intelligence Market in Venezuela: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.6.6. Artificial Intelligence Market in Other Latin American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
• 21.7. Data Triangulation and Validation

22. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN REST OF THE WORLD

• 22.1. Chapter Overview
• 22.2. Key Assumptions and Methodology
• 22.3. Revenue Shift Analysis
• 22.4. Market Movement Analysis
• 22.5. Penetration-Growth (P-G) Matrix
• 22.6. Artificial Intelligence Market in Rest of the World: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.6.1. Artificial Intelligence Market in Australia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.6.2. Artificial Intelligence Market in New Zealand: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.6.3. Artificial Intelligence Market in Other Countries
• 22.7. Data Triangulation and Validation

23. TABULATED DATA

24. LIST OF COMPANIES AND ORGANIZATIONS

25. CUSTOMIZATION OPPORTUNITIES

26. ROOTS SUBSCRIPTION SERVICES

27. AUTHOR DETAIL