查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1534202

全球因果人工智慧市場規模研究，依產品（平台、服務）、垂直產業（醫療保健與生命科學、BFSI、零售與電子商務、運輸與物流、製造、其他垂直產業）以及 2022-2032 年區域預測

Global Causal AI Market Size Study, by Offering (Platform, Services), by Vertical (Healthcare & Lifesciences, BFSI, Retail & eCommerce, Transportation & Logistics, Manufacturing, Other Verticals), and Regional Forecasts 2022-2032
出版日期: | 出版商: Bizwit Research & Consulting LLP | 英文 285 Pages | 商品交期: 2-3個工作天內

價格
簡介目錄

2023 年全球因果人工智慧市場價值約為 2,603 萬美元，預計在 2024-2032 年預測期內將以超過 40.98% 的健康成長率成長。因果人工智慧是人工智慧的一個分支，專注於理解和建模因果關係，而不僅僅是相關性。透過識別驅動觀察到的現象的潛在機制，因果人工智慧可以實現更準確的預測、更好的決策並增強對複雜系統的理解。它結合了統計學、機器學習和特定領域知識的方法來揭示因果關係，提供傳統人工智慧方法可能錯過的見解。這項技術在醫療保健、經濟和政策制定等領域特別有價值，在這些領域，理解因果關係對於有效的干涉措施和策略至關重要。

因果人工智慧作為克服當前人工智慧模型局限性的解決方案的出現以及人工智慧計劃的實施是市場成長的主要驅動力。在各個領域，因果推理模型的重要性越來越被認知。例如，在醫療保健領域，了解因果關係可以顯著提高患者的治療效果和治療效果。然而，從複雜的資料集中得出因果推論提出了巨大的挑戰，需要先進的演算法和運算能力。

市場研究涵蓋的關鍵區域包括亞太地區、北美、歐洲、拉丁美洲和世界其他地區。 2023 年，北美將在因果人工智慧的發展中發揮關鍵作用。對提供更深入見解和提高決策能力的複雜分析解決方案的需求不斷成長，正在推動市場向前發展。北美各國政府，特別是美國和加拿大政府，正在透過研究和創新的資金和資源分配，積極促進人工智慧技術的開發和採用。美國正透過國家標準與技術研究院 (NIST) 致力於制定人工智慧在醫療保健和金融等各個行業中應用的標準和指南。此外，預計亞太地區的市場在 2024 年至 2032 年的預測期內將以最快的速度發展。

目錄

第 1 章：全球因果人工智慧市場執行摘要

  • 全球因果人工智慧市場規模及預測（2022-2032）
  • 區域概要
  • 分部摘要
    • 透過提供
    • 按垂直方向
  • 主要趨勢
  • 經濟衰退的影響
  • 分析師推薦與結論

第 2 章：全球因果人工智慧市場定義與研究假設

  • 研究目的
  • 市場定義
  • 研究假設
    • 包容與排除
    • 限制
    • 供給側分析
      • 可用性
      • 基礎設施
      • 監管環境
      • 市場競爭
      • 經濟可行性（消費者的角度）
    • 需求面分析
      • 監理框架
      • 技術進步
      • 環境考慮
      • 消費者意識和接受度
  • 估算方法
  • 研究涵蓋的年份
  • 貨幣兌換率

第 3 章：全球因果人工智慧市場動態

  • 市場促進因素
    • 因果推理模型的重要性
    • 因果人工智慧的出現
    • 實施人工智慧計劃
  • 市場挑戰
    • 從複雜資料集進行因果推斷
  • 市場機會
    • 人工智慧技術的進步
    • 政府舉措
    • 不斷成長的投資

第 4 章：全球因果人工智慧市場產業分析

  • 波特的五力模型
    • 供應商的議價能力
    • 買家的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭競爭
    • 波特五力模型的未來方法
    • 波特的 5 力影響分析
  • PESTEL分析
    • 政治的
    • 經濟
    • 社會的
    • 技術性
    • 環境的
    • 合法的
  • 頂級投資機會
  • 最佳制勝策略
  • 顛覆性趨勢
  • 產業專家視角
  • 分析師推薦與結論

第 5 章：全球因果人工智慧市場規模與預測：按產品分類 - 2022-2032

  • 細分儀表板
  • 全球因果人工智慧市場：2022 年和 2032 年收入趨勢分析
    • 平台
    • 服務

第 6 章：全球因果人工智慧市場規模與預測：按垂直產業 - 2022-2032

  • 細分儀表板
  • 全球因果人工智慧市場：2022 年和 2032 年垂直收入趨勢分析
    • 醫療保健與生命科學
    • BFSI
    • 零售與電子商務
    • 運輸與物流
    • 製造業
    • 其他垂直領域

第 7 章：全球因果人工智慧市場規模與預測：按地區 - 2022-2032

  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 西班牙
    • 義大利
    • 歐洲其他地區
  • 亞太
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 韓國
    • 亞太地區其他地區
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 南非
    • 中東和非洲其他地區

第 8 章：競爭情報

  • 重點企業SWOT分析
  • 頂級市場策略
  • 公司簡介
    • IBM
      • 關鍵訊息
      • 概述
      • 財務（視數據可用性而定）
      • 產品概要
      • 市場策略
    • CausaLens
    • Microsoft
    • Causaly
    • Google
    • Geminos
    • AWS
    • Aitia
    • Xplain Data
    • INCRMNTAL
    • Logility
    • Cognino.ai

第 9 章：研究過程

  • 研究過程
    • 資料探勘
    • 分析
    • 市場預測
    • 驗證
    • 出版
  • 研究屬性
簡介目錄

Global Causal AI Market is valued approximately at USD 26.03 million in 2023 and is anticipated to grow with a healthy growth rate of more than 40.98% over the forecast period 2024-2032. Causal AI is a branch of artificial intelligence focused on understanding and modeling cause-and-effect relationships rather than just correlations. By identifying the underlying mechanisms driving observed phenomena, Causal AI enables more accurate predictions, better decision-making, and enhanced understanding of complex systems. It combines methods from statistics, machine learning, and domain-specific knowledge to uncover causality, offering insights that traditional AI approaches may miss. This technology is particularly valuable in fields such as healthcare, economics, and policy-making, where understanding causation is crucial for effective interventions and strategies.

The emergence of Causal AI as a solution to overcome the limitations of current AI models and the operationalizing of AI initiatives are primary drivers for market growth. In various fields, the importance of causal inference models is becoming increasingly recognized. For example, in healthcare, understanding causal relationships can significantly enhance patient outcomes and treatment efficacy. However, deriving causal inferences from complex data sets presents a substantial challenge, necessitating advanced algorithms and computational power.

The key regions considered for the market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. In 2023, North America is poised to play a pivotal role in the advancement of causal AI. The increasing demand for sophisticated analytics solutions that provide deeper insights and improve decision-making capabilities is propelling the market forward. Governments in North America, particularly in the United States and Canada, are actively promoting the development and adoption of AI technologies through funding and resource allocation for research and innovation. The United States, through the National Institute of Standards and Technology (NIST), is working on establishing standards and guidelines for the application of AI across various industries, including healthcare and finance. Furthermore, the market in Asia Pacific is anticipated to develop at the fastest rate over the forecast period 2024-2032.

Major market player included in this report are:

  • IBM
  • CausaLens
  • Microsoft
  • Causaly
  • Google
  • Geminos
  • AWS
  • Aitia
  • Xplain Data
  • INCRMNTAL
  • Logility
  • Cognino.ai

The detailed segments and sub-segment of the market are explained below:

By Offering:

  • Platform
  • Services

By Vertical:

  • Healthcare & Lifesciences
  • BFSI
  • Retail & eCommerce
  • Transportation & Logistics
  • Manufacturing
  • Other Verticals

By Region:

  • North America
  • U.S.
  • Canada
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Italy
  • ROE
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • RoAPAC
  • Latin America
  • Brazil
  • Mexico
  • RoLA
  • Middle East & Africa
  • Saudi Arabia
  • South Africa
  • RoMEA

Years considered for the study are as follows:

  • Historical year - 2022
  • Base year - 2023
  • Forecast period - 2024 to 2032

Key Takeaways:

  • Market Estimates & Forecast for 10 years from 2022 to 2032.
  • Annualized revenues and regional level analysis for each market segment.
  • Detailed analysis of geographical landscape with Country level analysis of major regions.
  • Competitive landscape with information on major players in the market.
  • Analysis of key business strategies and recommendations on future market approach.
  • Analysis of competitive structure of the market.
  • Demand side and supply side analysis of the market

Table of Contents

Chapter 1. Global Causal AI Market Executive Summary

  • 1.1. Global Causal AI Market Size & Forecast (2022-2032)
  • 1.2. Regional Summary
  • 1.3. Segmental Summary
    • 1.3.1. By Offering
    • 1.3.2. By Vertical
  • 1.4. Key Trends
  • 1.5. Recession Impact
  • 1.6. Analyst Recommendation & Conclusion

Chapter 2. Global Causal AI Market Definition and Research Assumptions

  • 2.1. Research Objective
  • 2.2. Market Definition
  • 2.3. Research Assumptions
    • 2.3.1. Inclusion & Exclusion
    • 2.3.2. Limitations
    • 2.3.3. Supply Side Analysis
      • 2.3.3.1. Availability
      • 2.3.3.2. Infrastructure
      • 2.3.3.3. Regulatory Environment
      • 2.3.3.4. Market Competition
      • 2.3.3.5. Economic Viability (Consumer's Perspective)
    • 2.3.4. Demand Side Analysis
      • 2.3.4.1. Regulatory frameworks
      • 2.3.4.2. Technological Advancements
      • 2.3.4.3. Environmental Considerations
      • 2.3.4.4. Consumer Awareness & Acceptance
  • 2.4. Estimation Methodology
  • 2.5. Years Considered for the Study
  • 2.6. Currency Conversion Rates

Chapter 3. Global Causal AI Market Dynamics

  • 3.1. Market Drivers
    • 3.1.1. Importance of Causal Inference Models
    • 3.1.2. Emergence of Causal AI
    • 3.1.3. Operationalizing AI Initiatives
  • 3.2. Market Challenges
    • 3.2.1. Causal Inference from Complex Data Sets
  • 3.3. Market Opportunities
    • 3.3.1. Advancements in AI Technologies
    • 3.3.2. Government Initiatives
    • 3.3.3. Growing Investments

Chapter 4. Global Causal AI Market Industry Analysis

  • 4.1. Porter's 5 Force Model
    • 4.1.1. Bargaining Power of Suppliers
    • 4.1.2. Bargaining Power of Buyers
    • 4.1.3. Threat of New Entrants
    • 4.1.4. Threat of Substitutes
    • 4.1.5. Competitive Rivalry
    • 4.1.6. Futuristic Approach to Porter's 5 Force Model
    • 4.1.7. Porter's 5 Force Impact Analysis
  • 4.2. PESTEL Analysis
    • 4.2.1. Political
    • 4.2.2. Economical
    • 4.2.3. Social
    • 4.2.4. Technological
    • 4.2.5. Environmental
    • 4.2.6. Legal
  • 4.3. Top investment opportunity
  • 4.4. Top winning strategies
  • 4.5. Disruptive Trends
  • 4.6. Industry Expert Perspective
  • 4.7. Analyst Recommendation & Conclusion

Chapter 5. Global Causal AI Market Size & Forecasts by Offering 2022-2032

  • 5.1. Segment Dashboard
  • 5.2. Global Causal AI Market: Offering Revenue Trend Analysis, 2022 & 2032 (USD Million)
    • 5.2.1. Platform
    • 5.2.2. Services

Chapter 6. Global Causal AI Market Size & Forecasts by Vertical 2022-2032

  • 6.1. Segment Dashboard
  • 6.2. Global Causal AI Market: Vertical Revenue Trend Analysis, 2022 & 2032 (USD Million)
    • 6.2.1. Healthcare & Lifesciences
    • 6.2.2. BFSI
    • 6.2.3. Retail & eCommerce
    • 6.2.4. Transportation & Logistics
    • 6.2.5. Manufacturing
    • 6.2.6. Other Verticals

Chapter 7. Global Causal AI Market Size & Forecasts by Region 2022-2032

  • 7.1. North America Causal AI Market
    • 7.1.1. U.S. Causal AI Market
      • 7.1.1.1. Offering breakdown size & forecasts, 2022-2032
      • 7.1.1.2. Vertical breakdown size & forecasts, 2022-2032
    • 7.1.2. Canada Causal AI Market
  • 7.2. Europe Causal AI Market
    • 7.2.1. U.K. Causal AI Market
    • 7.2.2. Germany Causal AI Market
    • 7.2.3. France Causal AI Market
    • 7.2.4. Spain Causal AI Market
    • 7.2.5. Italy Causal AI Market
    • 7.2.6. Rest of Europe Causal AI Market
  • 7.3. Asia-Pacific Causal AI Market
    • 7.3.1. China Causal AI Market
    • 7.3.2. India Causal AI Market
    • 7.3.3. Japan Causal AI Market
    • 7.3.4. Australia Causal AI Market
    • 7.3.5. South Korea Causal AI Market
    • 7.3.6. Rest of Asia Pacific Causal AI Market
  • 7.4. Latin America Causal AI Market
    • 7.4.1. Brazil Causal AI Market
    • 7.4.2. Mexico Causal AI Market
    • 7.4.3. Rest of Latin America Causal AI Market
  • 7.5. Middle East & Africa Causal AI Market
    • 7.5.1. Saudi Arabia Causal AI Market
    • 7.5.2. South Africa Causal AI Market
    • 7.5.3. Rest of Middle East & Africa Causal AI Market

Chapter 8. Competitive Intelligence

  • 8.1. Key Company SWOT Analysis
  • 8.2. Top Market Strategies
  • 8.3. Company Profiles
    • 8.3.1. IBM
      • 8.3.1.1. Key Information
      • 8.3.1.2. Overview
      • 8.3.1.3. Financial (Subject to Data Availability)
      • 8.3.1.4. Product Summary
      • 8.3.1.5. Market Strategies
    • 8.3.2. CausaLens
    • 8.3.3. Microsoft
    • 8.3.4. Causaly
    • 8.3.5. Google
    • 8.3.6. Geminos
    • 8.3.7. AWS
    • 8.3.8. Aitia
    • 8.3.9. Xplain Data
    • 8.3.10. INCRMNTAL
    • 8.3.11. Logility
    • 8.3.12. Cognino.ai

Chapter 9. Research Process

  • 9.1. Research Process
    • 9.1.1. Data Mining
    • 9.1.2. Analysis
    • 9.1.3. Market Estimation
    • 9.1.4. Validation
    • 9.1.5. Publishing
  • 9.2. Research Attributes