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封面
市场调查报告书
商品编码
1534202

全球因果人工智慧市场规模研究，依产品（平台、服务）、垂直产业（医疗保健与生命科学、BFSI、零售与电子商务、运输与物流、製造、其他垂直产业）以及 2022-2032 年区域预测

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个工作天内

价格
简介目录

2023 年全球因果人工智慧市场价值约为 2,603 万美元，预计在 2024-2032 年预测期内将以超过 40.98% 的健康成长率成长。因果人工智慧是人工智慧的一个分支，专注于理解和建模因果关係，而不仅仅是相关性。透过识别驱动观察到的现象的潜在机制，因果人工智慧可以实现更准确的预测、更好的决策并增强对复杂系统的理解。它结合了统计学、机器学习和特定领域知识的方法来揭示因果关係，提供传统人工智慧方法可能错过的见解。这项技术在医疗保健、经济和政策制定等领域特别有价值，在这些领域，理解因果关係对于有效的干预措施和策略至关重要。

因果人工智慧作为克服当前人工智慧模型局限性的解决方案的出现以及人工智慧计划的实施是市场成长的主要驱动力。在各个领域，因果推理模型的重要性越来越被认识。例如，在医疗保健领域，了解因果关係可以显着提高患者的治疗效果和治疗效果。然而，从复杂的资料集中得出因果推论提出了巨大的挑战，需要先进的演算法和运算能力。

市场研究考虑的关键区域包括亚太地区、北美、欧洲、拉丁美洲和世界其他地区。 2023 年，北美将在因果人工智慧的发展中发挥关键作用。对提供更深入见解和提高决策能力的复杂分析解决方案的需求不断增长，正在推动市场向前发展。北美各国政府，特别是美国和加拿大政府，正在透过研究和创新的资金和资源分配，积极促进人工智慧技术的开发和采用。美国正透过国家标准与技术研究院 (NIST) 致力于制定人工智慧在医疗保健和金融等各个行业中应用的标准和指南。此外，预计亚太地区的市场在 2024 年至 2032 年的预测期内将以最快的速度发展。

目录

第 1 章：全球因果人工智慧市场执行摘要

  • 全球因果人工智慧市场规模及预测（2022-2032）
  • 区域概要
  • 分部摘要
    • 透过提供
    • 按垂直方向
  • 主要趋势
  • 经济衰退的影响
  • 分析师推荐与结论

第 2 章：全球因果人工智慧市场定义与研究假设

  • 研究目的
  • 市场定义
  • 研究假设
    • 包容与排除
    • 限制
    • 供给侧分析
      • 可用性
      • 基础设施
      • 监管环境
      • 市场竞争
      • 经济可行性（消费者的角度）
    • 需求面分析
      • 监理框架
      • 技术进步
      • 环境考虑
      • 消费者意识和接受度
  • 估算方法
  • 研究考虑的年份
  • 货币兑换率

第 3 章：全球因果人工智慧市场动态

  • 市场驱动因素
    • 因果推理模型的重要性
    • 因果人工智慧的出现
    • 实施人工智慧计划
  • 市场挑战
    • 从复杂资料集进行因果推断
  • 市场机会
    • 人工智慧技术的进步
    • 政府倡议
    • 不断增长的投资

第 4 章：全球因果人工智慧市场产业分析

  • 波特的五力模型
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争竞争
    • 波特五力模型的未来方法
    • 波特的 5 力影响分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社会的
    • 技术性
    • 环境的
    • 合法的
  • 顶级投资机会
  • 最佳制胜策略
  • 颠覆性趋势
  • 产业专家视角
  • 分析师推荐与结论

第 5 章：全球因果人工智慧市场规模与预测：按产品分类 - 2022-2032

  • 细分仪表板
  • 全球因果人工智慧市场：2022 年和 2032 年收入趋势分析
    • 平台
    • 服务

第 6 章：全球因果人工智慧市场规模与预测：按垂直产业 - 2022-2032

  • 细分仪表板
  • 全球因果人工智慧市场：2022 年和 2032 年垂直收入趋势分析
    • 医疗保健与生命科学
    • BFSI
    • 零售与电子商务
    • 运输与物流
    • 製造业
    • 其他垂直领域

第 7 章：全球因果人工智慧市场规模与预测：按地区 - 2022-2032

  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 西班牙
    • 义大利
    • 欧洲其他地区
  • 亚太
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 韩国
    • 亚太地区其他地区
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 南非
    • 中东和非洲其他地区

第 8 章：竞争情报

  • 重点企业SWOT分析
  • 顶级市场策略
  • 公司简介
    • IBM
      • 关键讯息
      • 概述
      • 财务（视数据可用性而定）
      • 产品概要
      • 市场策略
    • CausaLens
    • Microsoft
    • Causaly
    • Google
    • Geminos
    • AWS
    • Aitia
    • Xplain Data
    • INCRMNTAL
    • Logility
    • Cognino.ai

第 9 章：研究过程

  • 研究过程
    • 资料探勘
    • 分析
    • 市场预测
    • 验证
    • 出版
  • 研究属性
简介目录

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