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全球因果 AI 市場：按產品（平台（部署（雲、本地））、服務）、行業（醫療/生命科學、BFSI、零售/電子商務、運輸/物流、製造）和區域預測（至 2030 年）
市場調查報告書
商品編碼
1279997

全球因果 AI 市場：按產品（平台（部署（雲、本地））、服務）、行業（醫療/生命科學、BFSI、零售/電子商務、運輸/物流、製造）和區域預測（至 2030 年）

Causal AI Market by Offering (Platforms (Deployment (Cloud and On-premises)) and Services), Vertical (Healthcare & Life Sciences, BFSI, Retail & eCommerce, Transportation & Logistics, Manufacturing) and Region - Global Forecast to 2030
出版日期: | 出版商: MarketsandMarkets | 英文 201 Pages | 訂單完成後即時交付

價格
簡介目錄

全球因果 AI 市場規模預計到 2030 年將達到 1.195 億美元，高於 2023 年的 801 萬美元，在預測期內以 47.1% 的複合年增長率增長。

因果 AI 是唯一能夠像人類一樣推理和做出選擇的技術。 它有可能徹底改變企業人工智能，使其更加透明、公平和安全。 對準確預測和決策制定的需求不斷增加，預計將推動市場發展。

醫療和生命科學將成為預測期內最大的行業市場

醫療和生命科學行業是世界上發展最快的行業之一，因果 AI 技術的採用正在增加。 Causal AI 和 Causal ML 在醫學和生命科學中用於藥物發現、患者診斷、治療和個性化醫療。 醫療領域先進技術的高采用率、幾家主要參與者的存在以及對個性化醫療不斷增長的需求是推動北美市場增長的因素。 由於越來越多地採用人工智能技術以及對創新醫療解決方案的需求不斷增加，預計歐洲也將顯著增長。 醫療和生命科學行業與因果人工智能技術相關的投資和收購正在激增。

通過部署，本地部分將在預測期內以最高複合年增長率增長

Causal AI Platform 的本地部署將軟件直接安裝到組織的服務器和硬件基礎設施上。 使用此部署模型，所有數據都存儲在您組織的網絡中，使您能夠最大程度地控制您的數據和平台。 具有嚴格數據隱私和法規遵從性要求的組織可能更喜歡內部部署，因為它們可以保持對其數據的完全控制。 內部部署還為與現有 IT 基礎設施的集成和定制提供了更大的潛力。

按服務劃分，培訓、支持和維護服務將在預測期內佔據最大的市場規模

Causal AI 的培訓、支持和維護服務為組織提供有效利用因果推理工具和技術所需的持續支持和專業知識。 這些服務專注於提供必要的教育、培訓和技術支持，以幫助組織從因果推理解決方案中獲得最大價值。 我們的培訓服務提供研討會和培訓課程，以幫助員工了解因果推理的基礎知識以及如何使用特定的軟件解決方案。 支持服務提供持續的技術支持，以幫助解決因果推理解決方案遇到的任何問題。 維護服務提供定期更新和維護，以確保您的軟件解決方案安全、可靠和有效。

按地區劃分，世界其他地區 (ROW) 將在預測期內實現最高的複合年增長率

因果 AI 市場正在全球迅速擴張，越來越多的公司和政府投資於這一新興技術。 在北美和歐洲之外，由於對高級數據分析的需求增加、AI 研發投資增加以及各行業採用基於 AI 的解決方案等各種因素，該市場也將顯著增長。 這些地區因果人工智能市場的主要趨勢之一是醫療保健、金融和零售等行業越來越多地採用基於人工智能的解決方案。

內容

第一章介紹

第二章研究方法論

第 3 章執行摘要

第 4 章重要注意事項

第 5 章市場概述和行業趨勢

  • 介紹
  • 市場動態
    • 司機
    • 約束因素
    • 機會
    • 任務
  • 案例研究分析
  • 生態系統分析
  • 使用因果 AI 的關鍵步驟
  • 基於關聯的 AI 與因果 AI
  • 技術分析
  • 因果 AI 市場最佳實踐
  • 因果 AI 情況的未來方向
  • 因果 AI 的發展簡史
  • 價值鏈分析
  • 定價模型分析
  • 專利分析
  • 波特的五力分析
  • 監管狀況
  • 主要利益相關者和採購標準
  • 影響因果 AI 市場中的買家/客戶的干擾
  • 主要會議和活動
  • 因果 AI 商業模式
  • 因果推理方法
  • 因果 AI 技術和方法

第 6 章因果 AI 市場：通過提供

  • 介紹
  • 平台
  • 服務
    • 諮詢服務
    • 安裝/集成
    • 培訓/支持/維護

第 7 章因果 AI 市場：按行業分類

  • 介紹
  • BFSI
  • 醫學和生命科學
  • 零售和電子商務
  • 製造業
  • 運輸和物流
  • 其他行業

第 8 章。因果 AI 市場：按地區

  • 介紹
  • 北美
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 其他歐洲
  • 其他地區（ROW）
    • 以色列
    • 中國
    • 日本
    • 其他行

第9章競爭格局

  • 概覽
  • 主要公司的戰略
  • 利潤分析
  • 市場份額分析
  • 公司評估象限
  • 競爭基準
  • 因果 AI 產品情況
  • 競爭場景

第十章公司簡介

  • 介紹
  • 主要公司
    • IBM
    • MICROSOFT
    • GOOGLE
    • AWS
    • DYNATRACE
    • H2O.AI
    • DATAROBOT
    • CAUSALENS
    • CAUSALITY LINK
    • AITIA
  • 其他主要企業
    • PARABOLE.AI
    • CAUSALIS
    • OMICS DATA AUTOMATION
    • INCRMNTAL
    • CAUSALY
    • LOGILITY
    • COGNINO.AI
    • COGNIZANT
    • SCALNYX
    • GEMINOS

第 11 章相鄰和相關市場

  • AI 治理市場
  • 人工智能 (AI) 市場

第十二章附錄

簡介目錄
Product Code: TC 8644

The market for Causal AI is projected to grow from USD 8010 thousand in 2023 to USD 119,500 thousand by 2030, at a CAGR of 47.1% during the forecast period. Causal AI is the only technology that can reason and make choices such as humans do. It has the potential to revolutionize enterprise AI, making it more transparent, fair, and safe. The increasing demand for accurate predictions and decision-making is expected to drive the market.

The Healthcare and Lifesciences vertical is projected to be the largest market during the forecast period

The healthcare and life sciences industry is one of the fastest-growing sectors in the world, and the adoption of causal AI technology is on the rise. Causal AI and Causal ML is used in healthcare and life sciences for drug discovery, patient diagnosis, treatment, personalized medicine, and more. The high adoption of advanced technologies in the healthcare sector, the presence of several key players, and the growing demand for personalized medicine are some of the factors driving the growth of the market in North America. Europe is also expected to grow significantly, driven by the increasing adoption of AI technology and the growing demand for innovative healthcare solutions. The healthcare and life sciences industry is witnessing a surge in investments and acquisitions related to causal AI technology.

Among deployment, on-premises segment is registered to grow at the highest CAGR during the forecast period

On-premises deployment of causal AI platforms involves installing the software directly onto the organization's servers or hardware infrastructure. This deployment model provides maximum control over the data and the platform, as all data is stored within the organization's own network. On-premises deployment may be preferred by organizations with strict data privacy or regulatory compliance requirements, as it allows them to maintain complete control over their data. On-premises deployment also offers the potential for greater customization and integration with existing IT infrastructure.

Among training, support, and maintenance services segment is anticipated to account for the largest market size during the forecast period

Causal AI training, support, and maintenance services provide organizations with the ongoing support and expertise they need to effectively leverage causal inference tools and techniques. These services focus on providing the education, training, and technical support necessary to ensure organizations can get the most value from their causal inference solutions. Training services involve providing workshops or training sessions to help employees understand the basics of causal inference and how to use specific software solutions. Whereas support services provide ongoing technical support to help organizations troubleshoot problems or issues that arise with their causal inference solutions. Maintenance services involve regularly updating and maintaining software solutions to ensure they remain secure, reliable, and effective.

Rest of World is projected to witness the highest CAGR during the forecast period.

The causal AI market is rapidly expanding globally, with a growing number of companies and governments investing in this emerging technology. In regions outside North America and Europe, the market is also experiencing significant growth, driven by various factors such as increasing demand for advanced data analytics, rising investments in AI research and development, and the adoption of AI-based solutions across various industries. One of the major trends in the causal AI market in these regions is the increasing adoption of AI-based solutions in sectors such as healthcare, finance, and retail.

Breakdown of primaries

In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the Causal AI market.

  • By Company: Tier I: 35%, Tier II: 45%, and Tier III: 20%
  • By Designation: C-Level Executives: 35%, Directors: 25%, and Others: 40%
  • By Region: APAC: 30%, Europe: 20%, North America: 45%, ROW: 5%

Major vendors offering Causal AI solutions and services across the globe are IBM (US), CausaLens (England), Microsoft (US), Causaly (England), Google (US), Geminos (US), AWS (US), Aitia (US), INCRMNTAL (Israel), Logility (US), Cognino.ai. (England), H2O.ai (US), DataRobot (US), Cognizant (US), Scalnyx (France), Causality Link (US), Dynatrace (US), Parabole.ai (US), Causalis.ai (Israel), and Omics Data Automation (US).

Research Coverage

The market study covers Causal AI across segments. It aims at estimating the market size and the growth potential across different segments, such as offering, vertical, and region. It includes an in-depth competitive analysis of the key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.

Key Benefits of Buying the Report

The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall market for Causal AI and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

  • Analysis of key drivers (Importance of Causal Inference Models in Various Fields, Emergence of Causal AI as a Solution to Overcome the Limitations of Current AI, Operationalizing AI initiatives), restraints (Lack of interpretability & explainability and Acquiring & preparing high-quality data), opportunities (Causal AI is its potential to revolutionize the field of healthcare and Technological advancements in Causal AI), and challenges (Causal Inference from Complex Data Sets, Lack of Standardization and Ethical and Legal Issues) influencing the growth of the Causal AI market
  • Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the Causal AI market.
  • Market Development: Comprehensive information about lucrative markets - the report analyses the Causal AI market across varied regions
  • Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in Causal AI and Causal ML market strategies; the report also helps stakeholders understand the pulse of the Causal AI market and provides them with information on key market drivers, restraints, challenges, and opportunities
  • Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players such as IBM (US), Google (US), AWS(US), Microsoft (US) Cognizant (US) and Dynatrace (US) among others in the Causal AI market.

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 STUDY OBJECTIVES
  • 1.2 MARKET DEFINITION
  • 1.3 INCLUSIONS AND EXCLUSIONS
  • 1.4 MARKET SCOPE
    • 1.4.1 MARKET SEGMENTATION
    • 1.4.2 REGIONS COVERED
    • 1.4.3 YEARS CONSIDERED
  • 1.5 CURRENCY CONSIDERED
    • TABLE 1 USD EXCHANGE RATES, 2020-2022
  • 1.6 STAKEHOLDERS

2 RESEARCH METHODOLOGY

  • 2.1 RESEARCH DATA
    • FIGURE 1 CAUSAL AI MARKET: RESEARCH DESIGN
    • 2.1.1 SECONDARY DATA
    • 2.1.2 PRIMARY DATA
      • 2.1.2.1 Primary interviews
      • 2.1.2.2 Breakup of primary profiles
      • 2.1.2.3 Key industry insights
  • 2.2 DATA TRIANGULATION
  • 2.3 MARKET SIZE ESTIMATION
    • FIGURE 2 CAUSAL AI MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
    • 2.3.1 TOP-DOWN APPROACH
    • 2.3.2 BOTTOM-UP APPROACH
    • FIGURE 3 APPROACH 1 (SUPPLY SIDE): REVENUE FROM OFFERING OF CAUSAL AI MARKET
    • FIGURE 4 APPROACH 2-BOTTOM-UP (SUPPLY SIDE): COLLECTIVE REVENUE FROM OFFERING OF CAUSAL AI PLAYERS
    • FIGURE 5 APPROACH 3-BOTTOM-UP (SUPPLY SIDE): REVENUE AND SUBSEQUENT MARKET ESTIMATION FROM OFFERING OF CAUSAL AI
    • FIGURE 6 APPROACH 4-BOTTOM-UP (DEMAND SIDE): SHARE OF CAUSAL AI OFFERING THROUGH OVERALL CAUSAL AI SPENDING
  • 2.4 MARKET FORECAST
    • TABLE 2 FACTOR ANALYSIS
  • 2.5 ASSUMPTIONS
    • TABLE 3 RESEARCH ASSUMPTIONS
  • 2.6 LIMITATIONS
  • 2.7 IMPLICATION OF RECESSION ON GLOBAL CAUSAL AI MARKET
    • TABLE 4 IMPACT OF RECESSION ON GLOBAL CAUSAL AI MARKET

3 EXECUTIVE SUMMARY

    • TABLE 5 CAUSAL AI MARKET SIZE AND GROWTH RATE, 2020-2022 (USD THOUSAND, Y-O-Y)
    • TABLE 6 CAUSAL AI MARKET SIZE AND GROWTH RATE, 2023-2030 (USD THOUSAND, Y-O-Y)
    • FIGURE 7 CAUSAL AI PLATFORMS TO ACCOUNT FOR LARGER MARKET THAN SERVICES IN 2023
    • FIGURE 8 CLOUD DEPLOYMENT TO ACCOUNT FOR LARGER MARKET SHARE IN 2023
    • FIGURE 9 CONSULTING SERVICES TO ACCOUNT FOR LARGEST MARKET IN 2023
    • FIGURE 10 HEALTHCARE & LIFESCIENCES VERTICAL TO ACCOUNT FOR LARGEST MARKET IN 2023
    • FIGURE 11 NORTH AMERICA ESTIMATED TO ACCOUNT FOR LARGEST SHARE IN 2023

4 PREMIUM INSIGHTS

  • 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN CAUSAL AI MARKET
    • FIGURE 12 HIGH DEMAND FOR PLATFORMS TO TRANSFER DATA FROM PHYSICAL PREMISES TO CLOUD
  • 4.2 CAUSAL AI MARKET, BY VERTICAL
    • FIGURE 13 HEALTHCARE & LIFE SCIENCES TO ACCOUNT FOR LARGEST SIZE DURING FORECAST PERIOD
  • 4.3 CAUSAL AI MARKET, BY REGION
    • FIGURE 14 NORTH AMERICA TO ACCOUNT FOR LARGEST SHARE BY 2028
  • 4.4 CAUSAL AI MARKET, BY OFFERING AND KEY VERTICAL
    • FIGURE 15 PLATFORMS AND HEALTHCARE & LIFE SCIENCES SEGMENTS TO ACCOUNT FOR SIGNIFICANT RESPECTIVE SHARES BY 2030

5 MARKET OVERVIEW AND INDUSTRY TRENDS

  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    • FIGURE 16 CAUSAL AI MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
    • 5.2.1 DRIVERS
      • 5.2.1.1 Importance of causal inference models in various fields
      • 5.2.1.2 Emergence of causal AI to overcome limitations of current AI
      • 5.2.1.3 Operationalizing AI initiatives
    • 5.2.2 RESTRAINTS
      • 5.2.2.1 Lack of interpretability and explainability
      • 5.2.2.2 Acquiring and preparing high-quality data
    • 5.2.3 OPPORTUNITIES
      • 5.2.3.1 Potential to revolutionize healthcare field
      • 5.2.3.2 Technological advancements
    • 5.2.4 CHALLENGES
      • 5.2.4.1 Causal inference from complex data sets
      • 5.2.4.2 Lack of standardization
  • 5.3 CASE STUDY ANALYSIS
    • 5.3.1 ACCELERATING MODEL VALIDATION WITH CAUSAL AI
    • 5.3.2 UNLOCKING REVENUE GROWTH WITH CAUSAL AI-POWERED PRICING AND PROMOTION OPTIMIZATION
    • 5.3.3 USING CAUSAL AI TO ENHANCE CUSTOMER RETENTION STRATEGIES
    • 5.3.4 REVOLUTIONIZING DATA PROVIDER INDUSTRY WITH CAUSAL AI
    • 5.3.5 USE OF CAUSAL AI FOR CUSTOMER SEGMENTATION
  • 5.4 ECOSYSTEM ANALYSIS
    • FIGURE 17 ECOSYSTEM ANALYSIS
    • TABLE 7 PLATFORM PROVIDERS
    • TABLE 8 LIBRARY PROVIDERS
    • TABLE 9 AI FRAMEWORK PROVIDERS
    • TABLE 10 REGULATORY BODIES
  • 5.5 KEY STEPS IN USING CAUSAL AI
    • 5.5.1 DATA COLLECTION & PREPARATION
    • 5.5.2 CAUSAL INFERENCE
    • 5.5.3 ML MODELS
    • 5.5.4 INTERPRETABILITY & EXPLAINABILITY
    • 5.5.5 VALIDATION & TESTING
  • 5.6 CORRELATION-BASED AI VS. CAUSAL AI
    • TABLE 11 CORRELATION-BASED AI VS. CAUSAL AI
  • 5.7 TECHNOLOGY ANALYSIS
    • 5.7.1 RELATED TECHNOLOGIES
      • 5.7.1.1 Supervised learning
      • 5.7.1.2 Unsupervised learning
      • 5.7.1.3 Natural language processing
      • 5.7.1.4 Predictive analytics
      • 5.7.1.5 Deep learning
      • 5.7.1.6 AI governance (ethical, explainable, and responsible AI)
      • 5.7.1.7 Bayesian networks
    • 5.7.2 ALLIED TECHNOLOGIES
      • 5.7.2.1 Cloud computing
      • 5.7.2.2 Robotics
      • 5.7.2.3 Federated learning
      • 5.7.2.4 Digital twin
  • 5.8 BEST PRACTICES IN CAUSAL AI MARKET
  • 5.9 FUTURE DIRECTIONS OF CAUSAL AI LANDSCAPE
    • TABLE 12 SHORT-TERM ROADMAP, 2023-2025
    • TABLE 13 MID-TERM ROADMAP, 2026-2028
    • TABLE 14 LONG-TERM ROADMAP, 2029-2030
  • 5.10 BRIEF HISTORY OF EVOLUTION OF CAUSAL AI
  • 5.11 VALUE CHAIN ANALYSIS
    • FIGURE 18 CAUSAL AI MARKET: VALUE CHAIN ANALYSIS
    • 5.11.1 DATA COLLECTION & PREPARATION
    • 5.11.2 ALGORITHM DEVELOPMENT
    • 5.11.3 MODEL TRAINING
    • 5.11.4 MODEL TESTING & VALIDATION
    • 5.11.5 DEPLOYMENT & INTEGRATION
    • 5.11.6 MAINTENANCE & SUPPORT
  • 5.12 PRICING MODEL ANALYSIS
    • TABLE 15 PRICING MODELS
  • 5.13 PATENT ANALYSIS
    • 5.13.1 METHODOLOGY
    • 5.13.2 DOCUMENT TYPE
    • TABLE 16 PATENTS FILED, 2013-2023
    • 5.13.3 INNOVATION & PATENT APPLICATIONS
    • FIGURE 19 TOTAL NUMBER OF PATENTS GRANTED, 2013-2023
      • 5.13.3.1 Top Applicants
    • FIGURE 20 TOP TEN COMPANIES WITH HIGHEST NUMBER OF PATENT APPLICATIONS, 2013-2022
    • TABLE 17 US: TOP 20 PATENT OWNERS, 2013-2022
    • TABLE 18 LIST OF PATENTS IN CAUSAL AI MARKET, 2021-2023
  • 5.14 PORTER'S FIVE FORCES ANALYSIS
    • FIGURE 21 PORTER'S FIVE FORCES ANALYSIS
    • TABLE 19 PORTER'S FIVE FORCES ANALYSIS
    • 5.14.1 THREAT FROM NEW ENTRANTS
    • 5.14.2 THREAT FROM SUBSTITUTES
    • 5.14.3 BARGAINING POWER OF SUPPLIERS
    • 5.14.4 BARGAINING POWER OF BUYERS
    • 5.14.5 INTENSITY OF COMPETITIVE RIVALRY
  • 5.15 REGULATORY LANDSCAPE
    • 5.15.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 20 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 21 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 22 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 23 ROW: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
      • 5.15.1.1 North America
        • 5.15.1.1.1 US
        • 5.15.1.1.2 Canada
      • 5.15.1.2 Europe
      • 5.15.1.3 Asia Pacific
        • 5.15.1.3.1 South Korea
        • 5.15.1.3.2 China
        • 5.15.1.3.3 India
      • 5.15.1.4 Middle East & Africa
        • 5.15.1.4.1 UAE
        • 5.15.1.4.2 KSA
        • 5.15.1.4.3 Bahrain
      • 5.15.1.5 Latin America
        • 5.15.1.5.1 Brazil
        • 5.15.1.5.2 Mexico
  • 5.16 KEY STAKEHOLDERS AND BUYING CRITERIA
    • 5.16.1 KEY STAKEHOLDERS IN BUYING PROCESS
    • FIGURE 22 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS IN TOP THREE VERTICALS
    • TABLE 24 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS IN TOP THREE VERTICALS
    • 5.16.2 BUYING CRITERIA
    • FIGURE 23 KEY BUYING CRITERIA IN TOP THREE VERTICALS
    • TABLE 25 KEY BUYING CRITERIA IN TOP THREE VERTICALS
  • 5.17 DISRUPTIONS IMPACTING BUYERS/CLIENTS IN CAUSAL AI MARKET
    • FIGURE 24 DISRUPTIONS IMPACTING BUYERS/CLIENTS
  • 5.18 KEY CONFERENCES & EVENTS
    • TABLE 26 DETAILED LIST OF CONFERENCES & EVENTS, 2023-2024
  • 5.19 BUSINESS MODELS OF CAUSAL AI
    • 5.19.1 POTENTIAL OUTCOME FRAMEWORK
    • 5.19.2 CAUSAL GRAPH MODEL
  • 5.20 APPROACHES TO CAUSAL INFERENCES
    • 5.20.1 CORRELATIONS
    • 5.20.2 CAUSATION
    • 5.20.3 INTERVENTIONS
    • 5.20.4 COUNTERFACTUALS
    • 5.20.5 SYSTEM MODELING
  • 5.21 CAUSAL AI TECHNIQUES & METHODS
    • 5.21.1 MACHINE LEARNING ALGORITHMS
      • 5.21.1.1 Regression-based methods
      • 5.21.1.2 Decision trees and random forests
      • 5.21.1.3 K-nearest neighbor algorithms
      • 5.21.1.4 Other ML algorithms
    • 5.21.2 BAYESIAN NETWORKS
      • 5.21.2.1 Directed acyclic graphs (DAGs)
      • 5.21.2.2 Structural causal models (SCMs)
      • 5.21.2.3 Counterfactual DAGs
      • 5.21.2.4 Other Bayesian networks
    • 5.21.3 STRUCTURAL EQUATION MODELS
      • 5.21.3.1 Path analysis (DAGs)
      • 5.21.3.2 Confirmatory factor analysis (CFA)
      • 5.21.3.3 Partial least squares (PLS)
      • 5.21.3.4 Other structural equation models
    • 5.21.4 COUNTERFACTUAL ANALYSIS
      • 5.21.4.1 Propensity score matching (PSM)
      • 5.21.4.2 Difference-in-Differences (DiD)
      • 5.21.4.3 Instrumental variables (IV)
      • 5.21.4.4 Regression discontinuity design (RDD)

6 CAUSAL AI MARKET, BY OFFERING

  • 6.1 INTRODUCTION
    • 6.1.1 OFFERING: CAUSAL AI MARKET DRIVERS
    • FIGURE 25 CAUSAL AI SERVICES MARKET TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
    • TABLE 27 CAUSAL AI MARKET, BY OFFERING, 2020-2022 (USD THOUSAND)
    • TABLE 28 CAUSAL AI MARKET, BY OFFERING, 2023-2030 (USD THOUSAND)
  • 6.2 PLATFORMS
    • 6.2.1 DEMAND FOR DATA-DRIVEN DECISION-MAKING AND MORE ACCURATE PREDICTIONS AND INSIGHTS
    • TABLE 29 PLATFORMS: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 30 PLATFORMS: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
    • 6.2.2 CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT
    • FIGURE 26 ON-PREMISE PLATFORM DEPLOYMENT TO WITNESS HIGHER CAGR DURING FORECAST PERIOD
    • TABLE 31 CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT, 2020-2022 (USD THOUSAND)
    • TABLE 32 CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT, 2023-2030 (USD THOUSAND)
      • 6.2.2.1 On-premises
        • 6.2.2.1.1 Potential for greater customization and integration
    • TABLE 33 ON-PREMISES: CAUSAL AI PLATFORMS MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 34 ON-PREMISES: CAUSAL AI PLATFORMS MARKET, BY REGION, 2023-2030 (USD THOUSAND)
      • 6.2.2.2 Cloud
        • 6.2.2.2.1 Potential for greater accessibility
    • TABLE 35 CLOUD: CAUSAL AI PLATFORMS MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 36 CLOUD: CAUSAL AI PLATFORMS MARKET, BY REGION, 2023-2030 (USD THOUSAND)
  • 6.3 SERVICES
    • 6.3.1 VALUABLE RESOURCES AVAILABLE FOR THOSE LACKING INTERNAL PROFICIENCY
    • FIGURE 27 TRAINING, SUPPORT, AND MAINTENANCE SERVICES TO ACCOUNT FOR LARGEST MARKET DURING FORECAST PERIOD
    • TABLE 37 CAUSAL AI MARKET, BY SERVICE, 2020-2022 (USD THOUSAND)
    • TABLE 38 CAUSAL AI MARKET, BY SERVICE, 2023-2030 (USD THOUSAND)
    • 6.3.2 CONSULTING SERVICES
      • 6.3.2.1 Expert guidance to make informed decisions and achieve better results
    • TABLE 39 CONSULTING SERVICES: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 40 CONSULTING SERVICES: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
    • 6.3.3 DEPLOYMENT & INTEGRATION
      • 6.3.3.1 Focus on practical aspects of implementing causal inference
    • TABLE 41 DEPLOYMENT & INTEGRATION: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 42 DEPLOYMENT & INTEGRATION: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
    • 6.3.4 TRAINING, SUPPORT, AND MAINTENANCE
      • 6.3.4.1 Need for ongoing training and support to ensure optimal model performance and accuracy
    • TABLE 43 TRAINING, SUPPORT, AND MAINTENANCE: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 44 TRAINING, SUPPORT, AND MAINTENANCE: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)

7 CAUSAL AI MARKET, BY VERTICAL

  • 7.1 INTRODUCTION
    • 7.1.1 VERTICAL: CAUSAL AI MARKET DRIVERS
    • FIGURE 28 HEALTHCARE & LIFE SCIENCES VERTICAL TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
    • TABLE 45 CAUSAL AI MARKET, BY VERTICAL, 2020-2022 (USD THOUSAND)
    • TABLE 46 CAUSAL AI MARKET, BY VERTICAL, 2023-2030 (USD THOUSAND)
  • 7.2 BFSI
    • 7.2.1 HIGHLY COMPETITIVE WITH SEVERAL OPERATIONAL PLAYERS
    • TABLE 47 BFSI: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 48 BFSI: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
    • 7.2.2 USE CASES: BFSI
  • 7.3 HEALTHCARE & LIFE SCIENCES
    • 7.3.1 INVESTMENT BY STARTUPS IN DEVELOPING BLOOD TESTS FOR EARLY CANCER DETECTION
    • TABLE 49 HEALTHCARE & LIFE SCIENCES: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 50 HEALTHCARE & LIFE SCIENCES: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
    • 7.3.2 USE CASES: HEALTHCARE & LIFE SCIENCES
  • 7.4 RETAIL & ECOMMERCE
    • 7.4.1 OPTIMIZING PRODUCT INVENTORY FOR RETAILERS AND DISCOVERY FOR CUSTOMERS
    • TABLE 51 RETAIL & ECOMMERCE: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 52 RETAIL & ECOMMERCE: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
    • 7.4.2 USE CASES: RETAIL & ECOMMERCE
  • 7.5 MANUFACTURING
    • 7.5.1 ANALYZING DATA FROM PRODUCTION PROCESSES TO IDENTIFY DEFECTS AND QUALITY ISSUES IN REAL TIME
    • TABLE 53 MANUFACTURING: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 54 MANUFACTURING: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
    • 7.5.2 USE CASES: MANUFACTURING
  • 7.6 TRANSPORTATION & LOGISTICS
    • 7.6.1 OPTIMIZING VEHICLE ROUTES, TRACKING SHIPMENTS IN REAL TIME, AND IMPROVING DELIVERY TIMES
    • TABLE 55 TRANSPORTATION & LOGISTICS: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 56 TRANSPORTATION & LOGISTICS: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
    • 7.6.2 USE CASES: TRANSPORTATION & LOGISTICS
  • 7.7 OTHER VERTICALS
    • TABLE 57 OTHER VERTICALS: CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 58 OTHER VERTICALS: CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)

8 CAUSAL AI MARKET, BY REGION

  • 8.1 INTRODUCTION
    • FIGURE 29 NORTH AMERICA TO BE LARGEST MARKET DURING FORECAST PERIOD
    • FIGURE 30 JAPAN TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
    • TABLE 59 CAUSAL AI MARKET, BY REGION, 2020-2022 (USD THOUSAND)
    • TABLE 60 CAUSAL AI MARKET, BY REGION, 2023-2030 (USD THOUSAND)
  • 8.2 NORTH AMERICA
    • 8.2.1 NORTH AMERICA: CAUSAL AI MARKET DRIVERS
    • 8.2.2 NORTH AMERICA: IMPACT OF RECESSION
    • FIGURE 31 NORTH AMERICA: MARKET SNAPSHOT
    • TABLE 61 NORTH AMERICA: CAUSAL AI MARKET, BY OFFERING, 2020-2022 (USD THOUSAND)
    • TABLE 62 NORTH AMERICA: CAUSAL AI MARKET, BY OFFERING, 2023-2030 (USD THOUSAND)
    • TABLE 63 NORTH AMERICA: CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT, 2020-2022 (USD THOUSAND)
    • TABLE 64 NORTH AMERICA: CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT, 2023-2030 (USD THOUSAND)
    • TABLE 65 NORTH AMERICA: CAUSAL AI MARKET, BY SERVICE, 2020-2022 (USD THOUSAND)
    • TABLE 66 NORTH AMERICA: CAUSAL AI MARKET, BY SERVICE, 2023-2030 (USD THOUSAND)
    • TABLE 67 NORTH AMERICA: CAUSAL AI MARKET, BY VERTICAL, 2020-2022 (USD THOUSAND)
    • TABLE 68 NORTH AMERICA: CAUSAL AI MARKET, BY VERTICAL, 2023-2030 (USD THOUSAND)
    • TABLE 69 NORTH AMERICA: CAUSAL AI MARKET, BY COUNTRY, 2020-2022 (USD THOUSAND)
    • TABLE 70 NORTH AMERICA: CAUSAL AI MARKET, BY COUNTRY, 2023-2030 (USD THOUSAND)
    • 8.2.3 US
      • 8.2.3.1 Research and investment by leading universities and organizations
    • 8.2.4 CANADA
      • 8.2.4.1 Rise in adoption of machine learning applications in various industries
  • 8.3 EUROPE
    • 8.3.1 EUROPE: CAUSAL AI MARKET DRIVERS
    • 8.3.2 EUROPE: IMPACT OF RECESSION
    • TABLE 71 EUROPE: CAUSAL AI MARKET, BY OFFERING, 2020-2022 (USD THOUSAND)
    • TABLE 72 EUROPE: CAUSAL AI MARKET, BY OFFERING, 2023-2030 (USD THOUSAND)
    • TABLE 73 EUROPE: CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT, 2020-2022 (USD THOUSAND)
    • TABLE 74 EUROPE: CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT, 2023-2030 (USD THOUSAND)
    • TABLE 75 EUROPE: CAUSAL AI MARKET, BY SERVICE, 2020-2022 (USD THOUSAND)
    • TABLE 76 EUROPE: CAUSAL AI MARKET, BY SERVICE, 2023-2030 (USD THOUSAND)
    • TABLE 77 EUROPE: CAUSAL AI MARKET, BY VERTICAL, 2020-2022 (USD THOUSAND)
    • TABLE 78 EUROPE: CAUSAL AI MARKET, BY VERTICAL, 2023-2030 (USD THOUSAND)
    • TABLE 79 EUROPE: CAUSAL AI MARKET, BY COUNTRY, 2020-2022 (USD THOUSAND)
    • TABLE 80 EUROPE: CAUSAL AI MARKET, BY COUNTRY, 2023-2030 (USD THOUSAND)
    • 8.3.3 UK
      • 8.3.3.1 Businesses increasingly seeking to leverage benefits of AI and ML
    • 8.3.4 GERMANY
      • 8.3.4.1 Strong IT infrastructure and robust regulatory framework
    • 8.3.5 FRANCE
      • 8.3.5.1 Thriving startup ecosystem
    • 8.3.6 REST OF EUROPE
  • 8.4 REST OF THE WORLD (ROW)
    • 8.4.1 REST OF THE WORLD: CAUSAL AI MARKET DRIVERS
    • 8.4.2 ROW: IMPACT OF RECESSION
    • TABLE 81 ROW: CAUSAL AI MARKET, BY OFFERING, 2020-2022 (USD THOUSAND)
    • TABLE 82 ROW: CAUSAL AI MARKET, BY OFFERING, 2023-2030 (USD THOUSAND)
    • TABLE 83 ROW: CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT, 2020-2022 (USD THOUSAND)
    • TABLE 84 ROW: CAUSAL AI PLATFORMS MARKET, BY DEPLOYMENT, 2023-2030 (USD THOUSAND)
    • TABLE 85 ROW: CAUSAL AI MARKET, BY SERVICE, 2020-2022 (USD THOUSAND)
    • TABLE 86 ROW: CAUSAL AI MARKET, BY SERVICE, 2023-2030 (USD THOUSAND)
    • TABLE 87 ROW: CAUSAL AI MARKET, BY VERTICAL, 2020-2022 (USD THOUSAND)
    • TABLE 88 ROW: CAUSAL AI MARKET, BY VERTICAL, 2023-2030 (USD THOUSAND)
    • TABLE 89 ROW: CAUSAL AI MARKET, BY COUNTRY, 2020-2022 (USD THOUSAND)
    • TABLE 90 ROW: CAUSAL AI MARKET, BY COUNTRY, 2023-2030 (USD THOUSAND)
    • 8.4.3 ISRAEL
      • 8.4.3.1 Adoption of AI-based solutions in healthcare
    • 8.4.4 CHINA
      • 8.4.4.1 Initiatives such as Next Generation Artificial Intelligence Development Plan
    • 8.4.5 JAPAN
      • 8.4.5.1 Dedicated research initiatives such as Artificial Intelligence Technology Strategy
    • 8.4.6 OTHERS IN ROW

9 COMPETITIVE LANDSCAPE

  • 9.1 OVERVIEW
  • 9.2 KEY PLAYER STRATEGIES
    • TABLE 91 OVERVIEW OF KEY PRODUCTS LAUNCHED BY PROMINENT PLAYERS IN CAUSAL AI MARKET
  • 9.3 REVENUE ANALYSIS
    • FIGURE 32 REVENUE ANALYSIS FOR KEY PUBLIC COMPANIES, 2020-2022 (USD MILLION)
  • 9.4 MARKET SHARE ANALYSIS
    • FIGURE 33 CAUSAL AI MARKET SHARE ANALYSIS FOR KEY PLAYERS, 2022
    • TABLE 92 OVERVIEW OF STRATEGIES DEPLOYED BY KEY PLAYERS IN CAUSAL AI MARKET
  • 9.5 COMPANY EVALUATION QUADRANT
    • 9.5.1 STARS
    • 9.5.2 EMERGING LEADERS
    • 9.5.3 PERVASIVE PLAYERS
    • 9.5.4 PARTICIPANTS
    • FIGURE 34 KEY CAUSAL AI MARKET PLAYERS, COMPANY EVALUATION MATRIX, 2023
  • 9.6 COMPETITIVE BENCHMARKING
    • TABLE 93 COMPETITIVE BENCHMARKING OF KEY PLAYERS, 2022
    • TABLE 94 DETAILED LIST OF KEY STARTUPS/SMES
    • TABLE 95 COMPETITIVE BENCHMARKING OF STARTUPS/SMES
  • 9.7 CAUSAL AI PRODUCT LANDSCAPE
    • 9.7.1 COMPARATIVE ANALYSIS OF CAUSAL AI PRODUCTS
    • TABLE 96 COMPARATIVE ANALYSIS OF CAUSAL AI PRODUCTS
    • FIGURE 35 COMPARATIVE ANALYSIS OF CAUSAL AI PRODUCTS
    • 9.7.2 VALUATION AND FINANCIAL METRICS OF KEY CAUSAL AI VENDORS
    • FIGURE 36 FINANCIAL METRICS OF KEY CAUSAL AI VENDORS
    • FIGURE 37 YTD PRICE TOTAL RETURN AND STOCK BETA OF KEY CAUSAL AI VENDORS
  • 9.8 COMPETITIVE SCENARIO
    • 9.8.1 PRODUCT LAUNCHES
    • TABLE 97 PRODUCT LAUNCHES, MAY 2021-FEBRUARY 2023
    • 9.8.2 DEALS
    • TABLE 98 DEALS, OCTOBER 2020-FEBRUARY 2023

10 COMPANY PROFILES

  • 10.1 INTRODUCTION
  • (Business overview, Products/Solutions/Services offered, Recent developments & MnM View)**
  • 10.2 KEY PLAYERS
    • 10.2.1 IBM
    • TABLE 99 IBM: BUSINESS OVERVIEW
    • FIGURE 38 IBM: COMPANY SNAPSHOT
    • TABLE 100 IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 101 IBM: PRODUCT LAUNCHES
    • TABLE 102 IBM: DEALS
    • 10.2.2 MICROSOFT
    • TABLE 103 MICROSOFT: BUSINESS OVERVIEW
    • FIGURE 39 MICROSOFT: COMPANY SNAPSHOT
    • TABLE 104 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 105 MICROSOFT: PRODUCT LAUNCHES
    • TABLE 106 MICROSOFT: DEALS
    • 10.2.3 GOOGLE
    • TABLE 107 GOOGLE: BUSINESS OVERVIEW
    • FIGURE 40 GOOGLE: FINANCIAL OVERVIEW
    • TABLE 108 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 109 GOOGLE: PRODUCT LAUNCHES
    • TABLE 110 GOOGLE: DEALS
    • 10.2.4 AWS
    • TABLE 111 AWS: BUSINESS OVERVIEW
    • FIGURE 41 AWS: FINANCIAL OVERVIEW
    • TABLE 112 AWS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 113 AWS: PRODUCT LAUNCHES
    • TABLE 114 AWS: DEALS
    • 10.2.5 DYNATRACE
    • TABLE 115 DYNATRACE: BUSINESS OVERVIEW
    • FIGURE 42 DYNATRACE: FINANCIAL OVERVIEW
    • TABLE 116 DYNATRACE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 117 DYNATRACE: PRODUCT LAUNCHES
    • TABLE 118 DYNATRACE: DEALS
    • 10.2.6 H2O.AI
    • TABLE 119 H2O.AI: BUSINESS OVERVIEW
    • TABLE 120 H2O.AI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 121 H2O.AI: PRODUCT LAUNCHES
    • TABLE 122 H2O.AI: DEALS
    • 10.2.7 DATAROBOT
    • TABLE 123 DATAROBOT: BUSINESS OVERVIEW
    • TABLE 124 DATAROBOT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 125 DATAROBOT: DEALS
    • 10.2.8 CAUSALENS
    • TABLE 126 CAUSALENS: BUSINESS OVERVIEW
    • TABLE 127 CAUSALENS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 128 CAUSALENS: PRODUCT LAUNCHES
    • TABLE 129 CAUSALENS: DEALS
    • 10.2.9 CAUSALITY LINK
    • TABLE 130 CAUSALITY LINK: BUSINESS OVERVIEW
    • TABLE 131 CAUSALITY LINK: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 132 CAUSALITY LINK: PRODUCT LAUNCHES
    • TABLE 133 CAUSALITY LINK: DEALS
    • 10.2.10 AITIA
    • TABLE 134 AITIA: BUSINESS OVERVIEW
    • TABLE 135 AITIA: PRODUCTS/SOLUTIONS/SERVICES OFFERED
    • TABLE 136 AITIA: PRODUCT LAUNCHES
    • TABLE 137 AITIA: DEALS
  • *Details on Business overview, Products/Solutions/Services offered, Recent developments & MnM View might not be captured in case of unlisted companies.
  • 10.3 OTHER KEY PLAYERS
    • 10.3.1 PARABOLE.AI
    • 10.3.2 CAUSALIS
    • 10.3.3 OMICS DATA AUTOMATION
    • 10.3.4 INCRMNTAL
    • 10.3.5 CAUSALY
    • 10.3.6 LOGILITY
    • 10.3.7 COGNINO.AI
    • 10.3.8 COGNIZANT
    • 10.3.9 SCALNYX
    • 10.3.10 GEMINOS

11 ADJACENT AND RELATED MARKETS

  • 11.1 AI GOVERNANCE MARKET
    • 11.1.1 MARKET DEFINITION
    • 11.1.2 MARKET OVERVIEW
    • TABLE 138 AI GOVERNANCE MARKET SIZE AND GROWTH RATE, 2020-2026 (USD MILLION, Y-O-Y%)
    • 11.1.3 AI GOVERNANCE, BY COMPONENT
    • TABLE 139 AI GOVERNANCE MARKET, BY COMPONENT, 2020-2026 (USD MILLION)
    • 11.1.4 AI GOVERNANCE MARKET, BY SOLUTION
    • TABLE 140 AI GOVERNANCE MARKET, BY SOLUTION, 2020-2026 (USD MILLION)
    • 11.1.5 AI GOVERNANCE MARKET, BY DEPLOYMENT MODE
    • TABLE 141 AI GOVERNANCE MARKET, BY DEPLOYMENT MODE, 2020-2026 (USD MILLION)
    • 11.1.6 AI GOVERNANCE MARKET, BY ORGANIZATION SIZE
    • TABLE 142 AI GOVERNANCE MARKET, BY ORGANIZATION SIZE, 2020-2026 (USD MILLION)
    • 11.1.7 AI GOVERNANCE MARKET, BY VERTICAL
    • TABLE 143 AI GOVERNANCE MARKET, BY VERTICAL, 2020-2026 (USD MILLION)
    • 11.1.8 AI GOVERNANCE MARKET, BY REGION
    • TABLE 144 AI GOVERNANCE MARKET, BY REGION, 2020-2026 (USD MILLION)
  • 11.2 ARTIFICIAL INTELLIGENCE MARKET
    • 11.2.1 MARKET DEFINITION
    • 11.2.2 MARKET OVERVIEW
    • 11.2.3 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING
    • TABLE 145 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2016-2021 (USD BILLION)
    • TABLE 146 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2022-2027 (USD BILLION)
    • 11.2.4 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY
    • TABLE 147 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2016-2021 (USD BILLION)
    • TABLE 148 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2022-2027 (USD BILLION)
    • 11.2.5 ARTIFICIAL INTELLIGENCE MARKET, BY DEPLOYMENT MODE
    • TABLE 149 ARTIFICIAL INTELLIGENCE MARKET, BY DEPLOYMENT MODE, 2016-2021 (USD BILLION)
    • TABLE 150 ARTIFICIAL INTELLIGENCE MARKET, BY DEPLOYMENT MODE, 2022-2027 (USD BILLION)
    • 11.2.6 ARTIFICIAL INTELLIGENCE MARKET, BY ORGANIZATION SIZE
    • TABLE 151 ARTIFICIAL INTELLIGENCE MARKET, BY ORGANIZATION, 2016-2021 (USD BILLION)
    • TABLE 152 ARTIFICIAL INTELLIGENCE MARKET, BY ORGANIZATION, 2022-2027 (USD BILLION)
    • 11.2.7 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION
    • TABLE 153 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2016-2021 (USD BILLION)
    • TABLE 154 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2022-2027 (USD BILLION)
    • 11.2.8 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL
    • TABLE 155 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2016-2021 (USD BILLION)
    • TABLE 156 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2022-2027 (USD BILLION)
    • 11.2.9 ARTIFICIAL INTELLIGENCE MARKET, BY REGION
    • TABLE 157 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2016-2021 (USD BILLION)
    • TABLE 158 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2022-2027 (USD BILLION)

12 APPENDIX

  • 12.1 DISCUSSION GUIDE
  • 12.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
  • 12.3 CUSTOMIZATION OPTIONS
  • 12.4 RELATED REPORTS
  • 12.5 AUTHOR DETAILS