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市場調查報告書
商品編碼
1752105

全球認知運算市場（至 2035 年）：按組件類型、技術類型、部署類型、企業類型、最終用戶類型、地區、行業趨勢和預測

Cognitive Computing Market, Till 2035: Distribution by Type of Component, Type of Technology, Type of Deployment, Type of Enterprise, Type of End User, and Geographical Regions: Industry Trends and Global Forecasts
出版日期: | 出版商: Roots Analysis | 英文 179 Pages | 商品交期: 2-10個工作天內

價格
簡介目錄

認知運算市場概覽

預計到 2035 年，全球認知運算市場規模將從目前的 508.5 億美元增至 7,838 億美元，在預測期內（截至 2035 年）的複合年增長率為 28.23%。

Cognitive Computing Market-IMG1

認知運算市場：成長與趨勢

認知運算是人工智慧的一個分支，它透過基於電腦的框架模擬人類的認知過程。該系統採用機器學習、自然語言處理、深度學習、自適應演算法、資料探勘和模式識別等多種技術來複製人腦的功能，從而實現更快速、更大規模的決策和問題解決能力。

認知運算的發展目標是賦予電腦解決通常需要人類思考的複雜問題的能力。與傳統計算不同，認知系統能夠根據使用者互動進行學習和調整，並在理解上下文和含義的同時處理和解讀自然語言。此外，它們的推理和複雜問題解決能力能夠透過檢查大量結構化和非結構化數據，發掘隱藏的洞見，並提出可能的解決方案和建議，從而促進複雜概念的詮釋。

隨著時間的推移，科技的不斷進步為提升電腦智慧開闢了新的機會。因此，認知運算市場正在快速發展並呈現顯著成長。人工智慧和機器學習等智慧技術在各行各業的日益普及，進一步推動了對認知運算解決方案的需求。這對於數據驅動的決策和大規模數據處理尤其有利。企業領導者意識到其尚未開發的潛力，正在逐步投資於技術開發。

受雲端運算整合度不斷提高、認知解決方案在醫療保健領域的應用日益廣泛以及技術的持續進步等多種因素的推動，預計認知運算市場在預測期內將大幅成長。

本報告提供全球認知式運算市場相關調查分析，與市場規模的估計機會分析，競爭情形，企業簡介，近幾年的發展等資訊。

目錄

章節1 報告概要

第1章 序文

第2章 調查手法

第3章 市場動態

第4章 宏觀經濟指標

章節2 定性知識和見識

第5章 摘要整理

第6章 簡介

第7章 法規情勢

章節3 市場概要

第8章 主要企業整體性資料庫

第9章 競爭情形

第10章 閒置頻段分析

第11章 企業的競爭力的分析

第12章 認知式運算市場上Start-Ups生態系統

章節4 企業簡介

第13章 企業簡介

  • 章概要
  • Acuiti
  • Alphabet
  • AWS
  • BurstIQ
  • Cisco
  • CognitiveScale
  • ColdLight Solutions
  • Expert System
  • E-Zest
  • Google
  • IBM
  • Microsoft
  • Numenta
  • Palantir Technologies
  • Red Skios
  • Saffron Technology
  • SAS
  • SparkCognition
  • TCS
  • Teradata
  • Vantage Labs
  • Vicarious
  • Virtusa

章節5 市場趨勢

第14章 大趨勢的分析

第15章 未滿足需求的分析

第16章 專利分析

第17章 近幾年的發展

章節6 市場機會分析

第18章 全球認知式運算市場

第19章 市場機會:各元件類型

第20章 市場機會:各技術類型

第21章 市場機會:各部署類型

第22章 市場機會:類別企業

第23章 市場機會:終端用戶類別

第24章 北美的認知式運算市場機會

第25章 歐洲的認知式運算市場機會

第26章 亞洲的認知式運算市場機會

第27章 中東·北非(MENA)的認知式運算市場機會

第28章 南美的認知式運算市場機會

第29章 其他地區的認知式運算市場機會

第30章 市場集中分析:各主要企業

第31章 鄰近市場的分析

章節7 策略工具

第32章 關鍵制勝策略

第33章 波特的五力分析

第34章 SWOT分析

第35章 價值鏈分析

第36章 Roots的策略性建議

章節8 其他的壟斷的知識和見識

第37章 來自1次調查的知識和見識

第38章 報告的結論

章節9 附錄

簡介目錄
Product Code: RAICT300154

Cognitive Computing Market Overview

As per Roots Analysis, the global cognitive computing market size is estimated to grow from USD 50.85 billion in the current year to USD 783.8 billion by 2035, at a CAGR of 28.23% during the forecast period, till 2035.

Cognitive Computing Market - IMG1

The opportunity for cognitive computing market has been distributed across the following segments:

Type of Component

  • Platform
  • Services

Type of Technology

  • Deep Learning
  • Machine Learning
  • Natural Language Processing
  • Others

Type of Deployment

  • Cloud-based
  • On-premises

Type of Enterprise

  • Large Enterprises
  • Small & Medium Enterprises

Type of End User

  • BFSI
  • Government and Defense
  • Healthcare
  • IT & Telecommunication
  • Media & Entertainment
  • Retail & E-commerce
  • Others

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

COGNITIVE COMPUTING MARKET: GROWTH AND TRENDS

Cognitive computing is a sector of artificial intelligence that mimics human cognitive processes through a computer-based framework. This system employs a variety of technologies, including machine learning, natural language processing, deep learning, self-adaptive algorithms, data mining, and pattern recognition to replicate the functioning of the human brain, enabling quicker decision-making and problem-solving abilities on a larger scale.

The aim of cognitive computing development is to equip computers with the ability to deal with intricate issues that typically require human thinking. Unlike conventional computing, cognitive systems can learn and adjust based on user interactions, as well as process and interpret natural language while grasping context and meaning. Additionally, their reasoning and intricate problem-solving skills facilitate the resolution of complex concepts by examining vast amounts of structured and unstructured data, revealing hidden insights, and presenting possible solutions or recommendations.

With time, ongoing advancements in technology have opened up new opportunities for enhancing computer intelligence. As a result, the cognitive computing market is rapidly evolving and experiencing significant growth. The increasing adoption of smart technologies such as artificial intelligence and machine learning across various industries is further driving the demand for cognitive computing solutions. This is particularly beneficial for data-driven decision-making and large-scale data processing. Acknowledging its unexploited potential, business leaders are progressively investing in technological development.

Driven by various factors such as an increase in cloud computing integration, rise in the application of cognitive solutions in healthcare, and continuous technological progress, the cognitive computing market is expected to witness significant growth during the forecast period.

COGNITIVE COMPUTING MARKET: KEY SEGMENTS

Market Share by Type of Component

Based on type of component, the global cognitive computing market is segmented into platform and service. According to our estimates, currently, platform segment captures the majority share of the market. This can be attributed to the growing adoption of advanced analytics platforms in various industries, allowing organizations to scale their cognitive computing solutions according to their needs. The key features driving demand for this component include its scalability, flexibility, and integration capabilities, which enable businesses to begin and expand their cognitive solutions without significant investments in on-premises infrastructure.

However, the service component is anticipated to grow at a relatively higher CAGR during the forecast period. This growth can be linked to the rising demand and initiatives taken by companies to reduce cognitive analytics timelines by utilizing sophisticated cognitive services.

Market Share by Type of Technology

Based on type of technology, the cognitive computing market is segmented into deep learning, machine learning, natural language processing, and others. According to our estimates, currently, natural language processing segment captures the majority of the market. This can be attributed to its fundamental capability to facilitate a more intuitive and meaningful interaction between humans and computers by interpreting and comprehending human language. Additionally, the rise of conversational AI, text analytics, sentiment analysis, and document automation is driving the demand for natural language processing.

However, the machine learning segment is anticipated to grow at a relatively higher CAGR during the forecast period.

Market Share by Type of Deployment

Based on type of deployment, the cognitive computing market is segmented into cloud-based and on-premises. According to our estimates, currently, cloud based segment captures the majority share of the market. This can be attributed to its ability to adjust cognitive computing capabilities in response to demand while maintaining reasonable costs. Moreover, its availability enables organizations to implement cognitive computing applications among distributed teams and in remote settings.

However, the on-premises deployment segment is anticipated to grow at a relatively higher CAGR during the forecast period. This is due to the rising need from large enterprises to enhance the management of their extensive data with improved security.

Market Share by Type of Enterprise

Based on type of enterprise, the cognitive computing market is segmented into large enterprises and small and medium enterprises. According to our estimates, currently, large enterprise segment captures the majority share of the market. This can be attributed to the rise in adoption of advanced cognitive computing technologies and the integration of machine learning applications and IoT.

However, the small and medium enterprises segment is anticipated to grow at a relatively higher CAGR during the forecast period. This surge can be linked to the increased use of cloud computing, owing to its cost-effectiveness, which reduces the reliance on costly on-premises hardware and lowers operational expenses, along with facilitating smaller-scale implementations.

Market Share by Type of End User

Based on type of end user, the cognitive computing market is segmented into BFSI, government and defense, healthcare, it & telecommunication, media & entertainment, retail & e-commerce, and others. According to our estimates, currently, BFSI segment captures the majority share of the market. This can be attributed to the increasing demand for fraud detection and risk management, driven by the substantial amount of transactional and behavioral data. To meet this need, the industry requires cognitive computing systems that facilitate real-time data processing for identifying fraudulent activities and potential security threats.

In addition, the healthcare industry is widely embracing cognitive computing for purposes such as disease diagnosis and treatment, personalized medicine, medical research, and drug discovery. Further, its automated reasoning capabilities are beneficial for predictive analytics, which can anticipate public health trends and identify at-risk populations, making it extensively utilized in the field. Consequently, this segment is projected to experience a relatively higher CAGR during the forecast period.

Market Share by Geographical Regions

Based on geographical regions, the cognitive computing market is segmented into North America, Europe, Asia, Latin America, Middle East and North Africa, and the rest of the world. According to our estimates, currently, North America captures the majority share of the market. However, Asia is anticipated to experience a higher compound annual growth rate (CAGR) during the forecast period, driven by increasing industrialization, the rise of startup companies, and a significant adoption of enterprise cognitive systems in the area.

Example Players in Cognitive Computing Market

  • Acuiti
  • Alphabet
  • AWS
  • BurstlQ
  • Cisco
  • CognitiveScale
  • ColdLight Solutions
  • Expert System
  • E-Zest
  • Google
  • IBM
  • Microsoft
  • Numenta
  • Palantir Technologies
  • Red Skios
  • Saffron
  • SAS
  • SparkCognition
  • TCS
  • Teradata
  • Vantage Labs
  • Vicarious
  • Virtusa

COGNITIVE COMPUTING MARKET: RESEARCH COVERAGE

The report on the cognitive computing market features insights on various sections, including:

  • Market Sizing and Opportunity Analysis: An in-depth analysis of the cognitive computing market, focusing on key market segments, including [A] type of component, [B] type of technology, [C] type of deployment, [D] type of enterprise, [E] type of end user, and [F] geographical regions.
  • Competitive Landscape: A comprehensive analysis of the companies engaged in the cognitive computing market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters and [D] ownership structure.
  • Company Profiles: Elaborate profiles of prominent players engaged in the cognitive computing 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] cognitive computing portfolio, [J] moat analysis, [K] recent developments, and an informed future outlook.
  • Megatrends: An evaluation of ongoing megatrends in cognitive computing industry.
  • Patent Analysis: An insightful analysis of patents filed / granted in the cognitive computing domain, based on relevant parameters, including [A] type of patent, [B] patent publication year, [C] patent age and [D] leading players.
  • Recent Developments: An overview of the recent developments made in the cognitive computing market, along with analysis based on relevant parameters, including [A] year of initiative, [B] type of initiative, [C] geographical distribution and [D] most active players.
  • Porter's Five Forces Analysis: An analysis of five competitive forces prevailing in the cognitive computing market, including threats of new entrants, bargaining power of buyers, bargaining power of suppliers, threats of substitute products and rivalry among existing competitors.
  • 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 cognitive computing market?
  • Which are the leading companies in this 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?

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
  • 15% 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

SECTION I: REPORT OVERVIEW

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. MARKET DYNAMICS

  • 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

SECTION II: QUALITATIVE INSIGHTS

5. EXECUTIVE SUMMARY

6. INTRODUCTION

  • 6.1. Chapter Overview
  • 6.2. Overview of Cognitive Computing Market
    • 6.2.1. Type of Component
    • 6.2.2. Type of Technology
    • 6.2.3. Type of Deployment
    • 6.2.4. Type of Enterprise
  • 6.3. Future Perspective

7. REGULATORY SCENARIO

SECTION III: MARKET OVERVIEW

8. COMPREHENSIVE DATABASE OF LEADING PLAYERS

9. COMPETITIVE LANDSCAPE

  • 9.1. Chapter Overview
  • 9.2. Cognitive Computing: Overall Market Landscape
    • 9.2.1. Analysis by Year of Establishment
    • 9.2.2. Analysis by Company Size
    • 9.2.3. Analysis by Location of Headquarters
    • 9.2.4. Analysis by Ownership Structure

10. WHITE SPACE ANALYSIS

11. COMPANY COMPETITIVENESS ANALYSIS

12. STARTUP ECOSYSTEM IN THE COGNITIVE COMPUTING MARKET

  • 12.1. Cognitive Computing: Market Landscape of Startups
    • 12.1.1. Analysis by Year of Establishment
    • 12.1.2. Analysis by Company Size
    • 12.1.3. Analysis by Company Size and Year of Establishment
    • 12.1.4. Analysis by Location of Headquarters
    • 12.1.5. Analysis by Company Size and Location of Headquarters
    • 12.1.6. Analysis by Ownership Structure
  • 12.2. Key Findings

SECTION IV: COMPANY PROFILES

13. COMPANY PROFILES

  • 13.1. Chapter Overview
  • 13.2. Acuiti*
    • 13.2.1. Company Overview
    • 13.2.2. Company Mission
    • 13.2.3. Company Footprint
    • 13.2.4. Management Team
    • 13.2.5. Contact Details
    • 13.2.6. Financial Performance
    • 13.2.7. Operating Business Segments
    • 13.2.8. Service / Product Portfolio (project specific)
    • 13.2.9. MOAT Analysis
    • 13.2.10. Recent Developments and Future Outlook
  • 13.3. Alphabet
  • 13.4. AWS
  • 13.5. BurstIQ
  • 13.6. Cisco
  • 13.7. CognitiveScale
  • 13.8. ColdLight Solutions
  • 13.9. Expert System
  • 13.10. E-Zest
  • 13.11. Google
  • 13.12. IBM
  • 13.13. Microsoft
  • 13.14. Numenta
  • 13.15. Palantir Technologies
  • 13.16. Red Skios
  • 13.17. Saffron Technology
  • 13.18. SAS
  • 13.19. SparkCognition
  • 13.20. TCS
  • 13.21. Teradata
  • 13.22. Vantage Labs
  • 13.23. Vicarious
  • 13.24. Virtusa

SECTION V: MARKET TRENDS

14. MEGA TRENDS ANALYSIS

15. UNMEET NEED ANALYSIS

16. PATENT ANALYSIS

17. RECENT DEVELOPMENTS

  • 17.1. Chapter Overview
  • 17.2. Recent Funding
  • 17.3. Recent Partnerships
  • 17.4. Other Recent Initiatives

SECTION VI: MARKET OPPORTUNITY ANALYSIS

18. GLOBAL COGNITIVE COMPUTING MARKET

  • 18.1. Chapter Overview
  • 18.2. Key Assumptions and Methodology
  • 18.3. Trends Disruption Impacting Market
  • 18.4. Demand Side Trends
  • 18.5. Supply Side Trends
  • 18.6. Global Cognitive Computing, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.7. Multivariate Scenario Analysis
    • 18.7.1. Conservative Scenario
    • 18.7.2. Optimistic Scenario
  • 18.8. Investment Feasibility Index
  • 18.9. Key Market Segmentations

19. MARKET OPPORTUNITIES BASED ON TYPE OF COMPONENT

  • 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. Cognitive Computing Market for Platform: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.7. Cognitive Computing Market for Service: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.8. Data Triangulation and Validation
    • 19.8.1. Secondary Sources
    • 19.8.2. Primary Sources
    • 19.8.3. Statistical Modeling

20. MARKET OPPORTUNITIES BASED ON TYPE OF TECHNOLOGY

  • 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. Cognitive Computing Market for Deep Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.7. Cognitive Computing Market for Machine Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.8. Cognitive Computing Market for Natural Language Processing: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.9. Cognitive Computing Market for Other: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.10. Data Triangulation and Validation
    • 20.10.1. Secondary Sources
    • 20.10.2. Primary Sources
    • 20.10.3. Statistical Modeling

21. MARKET OPPORTUNITIES BASED ON TYPE OF DEPLOYMENT

  • 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. Cognitive Computing Market for Cloud-Based: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.7. Cognitive Computing Market for On-Premises: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.8. Data Triangulation and Validation
    • 21.8.1. Secondary Sources
    • 21.8.2. Primary Sources
    • 21.8.3. Statistical Modeling

22. MARKET OPPORTUNITIES BASED ON TYPE OF ENTERPRISE

  • 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. Cognitive Computing Market for Large Enterprise: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.7. Cognitive Computing Market for Small and Medium Enterprise: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.8. Data Triangulation and Validation
    • 22.8.1. Secondary Sources
    • 22.8.2. Primary Sources
    • 22.8.3. Statistical Modeling

23. MARKET OPPORTUNITIES BASED ON TYPE OF END USER

  • 23.1. Chapter Overview
  • 23.2. Key Assumptions and Methodology
  • 23.3. Revenue Shift Analysis
  • 23.4. Market Movement Analysis
  • 23.5. Penetration-Growth (P-G) Matrix
  • 23.6. Cognitive Computing Market for BFSI: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.7. Cognitive Computing Market for Government and Defense: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.8. Cognitive Computing Market for Healthcare: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.9. Cognitive Computing Market for IT & Telecommunication: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.10. Cognitive Computing Market for Media & Entertainment: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.11. Cognitive Computing Market for Retail & E-commerce: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.12. Cognitive Computing Market for Others: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.13. Data Triangulation and Validation
    • 23.13.1. Secondary Sources
    • 23.13.2. Primary Sources
    • 23.13.3. Statistical Modeling

24. MARKET OPPORTUNITIES FOR COGNITIVE COMPUTING IN NORTH AMERICA

  • 24.1. Chapter Overview
  • 24.2. Key Assumptions and Methodology
  • 24.3. Revenue Shift Analysis
  • 24.4. Market Movement Analysis
  • 24.5. Penetration-Growth (P-G) Matrix
  • 24.6. Cognitive Computing Market in North America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.1. Cognitive Computing Market in the US: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.2. Cognitive Computing Market in Canada: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.3. Cognitive Computing Market in Mexico: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.4. Cognitive Computing Market in Other North American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 24.7. Data Triangulation and Validation

25. MARKET OPPORTUNITIES FOR COGNITIVE COMPUTING IN EUROPE

  • 25.1. Chapter Overview
  • 25.2. Key Assumptions and Methodology
  • 25.3. Revenue Shift Analysis
  • 25.4. Market Movement Analysis
  • 25.5. Penetration-Growth (P-G) Matrix
  • 25.6. Cognitive Computing Market in Europe: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.1. Cognitive Computing Market in Austria: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.2. Cognitive Computing Market in Belgium: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.3. Cognitive Computing Market in Denmark: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.4. Cognitive Computing Market in France: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.5. Cognitive Computing Market in Germany: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.6. Cognitive Computing Market in Ireland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.7. Cognitive Computing Market in Italy: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.8. Cognitive Computing Market in the Netherlands: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.9. Cognitive Computing Market in Norway: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.10. Cognitive Computing Market in Russia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.11. Cognitive Computing Market in Spain: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.12. Cognitive Computing Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.13. Cognitive Computing Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.14. Cognitive Computing Market in Switzerland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.15. Cognitive Computing Market in the UK: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.16. Cognitive Computing Market in Other European Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 25.7. Data Triangulation and Validation

26. MARKET OPPORTUNITIES FOR COGNITIVE COMPUTING IN ASIA

  • 26.1. Chapter Overview
  • 26.2. Key Assumptions and Methodology
  • 26.3. Revenue Shift Analysis
  • 26.4. Market Movement Analysis
  • 26.5. Penetration-Growth (P-G) Matrix
  • 26.6. Cognitive Computing Market in Asia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.1. Cognitive Computing Market in China: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.2. Cognitive Computing Market in India: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.3. Cognitive Computing Market in Japan: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.4. Cognitive Computing Market in Singapore: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.5. Cognitive Computing Market in South Korea: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.6. Cognitive Computing Market in Other Asian Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 26.7. Data Triangulation and Validation

27. MARKET OPPORTUNITIES FOR COGNITIVE COMPUTING IN MIDDLE EAST AND NORTH AFRICA (MENA)

  • 27.1. Chapter Overview
  • 27.2. Key Assumptions and Methodology
  • 27.3. Revenue Shift Analysis
  • 27.4. Market Movement Analysis
  • 27.5. Penetration-Growth (P-G) Matrix
  • 27.6. Cognitive Computing Market in Middle East and North Africa (MENA): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.1. Cognitive Computing Market in Egypt: Historical Trends (Since 2019) and Forecasted Estimates (Till 205)
    • 27.6.2. Cognitive Computing Market in Iran: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.3. Cognitive Computing Market in Iraq: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.4. Cognitive Computing Market in Israel: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.5. Cognitive Computing Market in Kuwait: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.6. Cognitive Computing Market in Saudi Arabia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.7. Neuromorphic Computing Marke in United Arab Emirates (UAE): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.8. Cognitive Computing Market in Other MENA Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 27.7. Data Triangulation and Validation

28. MARKET OPPORTUNITIES FOR COGNITIVE COMPUTING IN LATIN AMERICA

  • 28.1. Chapter Overview
  • 28.2. Key Assumptions and Methodology
  • 28.3. Revenue Shift Analysis
  • 28.4. Market Movement Analysis
  • 28.5. Penetration-Growth (P-G) Matrix
  • 28.6. Cognitive Computing Market in Latin America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.1. Cognitive Computing Market in Argentina: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.2. Cognitive Computing Market in Brazil: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.3. Cognitive Computing Market in Chile: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.4. Cognitive Computing Market in Colombia Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.5. Cognitive Computing Market in Venezuela: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.6. Cognitive Computing Market in Other Latin American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 28.7. Data Triangulation and Validation

29. MARKET OPPORTUNITIES FOR COGNITIVE COMPUTING IN REST OF THE WORLD

  • 29.1. Chapter Overview
  • 29.2. Key Assumptions and Methodology
  • 29.3. Revenue Shift Analysis
  • 29.4. Market Movement Analysis
  • 29.5. Penetration-Growth (P-G) Matrix
  • 29.6. Cognitive Computing Market in Rest of the World: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.1. Cognitive Computing Market in Australia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.2. Cognitive Computing Market in New Zealand: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.3. Cognitive Computing Market in Other Countries
  • 29.7. Data Triangulation and Validation

30. MARKET CONCENTRATION ANALYSIS: DISTRIBUTION BY LEADING PLAYERS

  • 30.1. Leading Player 1
  • 30.2. Leading Player 2
  • 30.3. Leading Player 3
  • 30.4. Leading Player 4
  • 30.5. Leading Player 5
  • 30.6. Leading Player 6
  • 30.7. Leading Player 7
  • 30.8. Leading Player 8

31. ADJACENT MARKET ANALYSIS

SECTION VII: STRATEGIC TOOLS

32. KEY WINNING STRATEGIES

33. PORTER'S FIVE FORCES ANALYSIS

34. SWOT ANALYSIS

35. VALUE CHAIN ANALYSIS

36. ROOTS STRATEGIC RECOMMENDATIONS

  • 36.1. Chapter Overview
  • 36.2. Key Business-related Strategies
    • 36.2.1. Research & Development
    • 36.2.2. Product Manufacturing
    • 36.2.3. Commercialization / Go-to-Market
    • 36.2.4. Sales and Marketing
  • 36.3. Key Operations-related Strategies
    • 36.3.1. Risk Management
    • 36.3.2. Workforce
    • 36.3.3. Finance
    • 36.3.4. Others

SECTION VIII: OTHER EXCLUSIVE INSIGHTS

37. INSIGHTS FROM PRIMARY RESEARCH

38. REPORT CONCLUSION

SECTION IX: APPENDIX

39. TABULATED DATA

40. LIST OF COMPANIES AND ORGANIZATIONS

41. CUSTOMIZATION OPPORTUNITIES

42. ROOTS SUBSCRIPTION SERVICES

43. AUTHOR DETAILS