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市场调查报告书
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全球医疗保健领域生成式人工智慧市场：预测至 2032 年—按解决方案类型、监管领域、部署方式、组织规模、最终用户和地区进行分析

Generative AI in Healthcare Market Forecasts to 2032 - Global Analysis By Solution Types, Regulatory Domains, Deployment Modes, Organization Sizes, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，预计 2025 年全球医疗保健领域的生成式人工智慧市场规模将达到 28 亿美元，到 2032 年将达到 201 亿美元，预测期内复合年增长率将达到 32.1%。

医疗保健领域的生成式人工智慧是指利用先进的人工智慧系统，透过学习大量医疗数据中的模式，创造新的内容、洞见或解决方案。这些人工智慧模型可以产生合成医学影像、模拟患者预后、设计个人化治疗方案，并辅助药物研发。透过分析电子健康记录、基因组学和临床研究，生成式人工智慧能够支援预测性诊断、精准医疗和医学教育。其功能可增强决策能力、加速研究、降低成本，并促进整个医疗保健生态系统中患者照护和创新的提升。

提高营运效率和降低成本

医院和保险公司正在采用人工智慧来实现文件自动化、简化诊断流程并降低行政成本。生成模型透过合成数据和个人化内容，正在改善临床决策支援和病人参与。与电子病历和工作流程工具的整合正在提高可用性和速度。医疗保健专业人员正在利用人工智慧来优化资源分配并减少职业倦怠。这些效率提升正在推动人工智慧在医疗保健领域的广泛应用。

偏见和公平性问题

基于非代表性资料集训练的模型可能会产生扭曲的输出结果，进而影响诊断和治疗。模型逻辑缺乏透明度会使检验和监督变得复杂。结果差异可能会加剧患者群体中存在的系统性不平等。开发者也面临监管机构和伦理委员会的审查。这些风险持续限制高风险应用的普及。

临床试验进展

人工智慧正在产生合成对照组并模拟试验结果，以减少时间和成本。自然语言模型正在实现方案设计和合格筛检的自动化。与真实数据的整合正在提高试验的多样性和预测准确性。申办方正在利用人工智慧优化研究中心的选择和病人参与。这些创新正在推动临床研究的变革。

不愿聘用医疗专业人员

对准确性、责任归属和人员流动等方面的担忧正在减缓人工智慧技术的普及。许多临床医生没有接受过解读和检验人工智慧产生结果的培训。由于缺乏可解释性和监督机制，人们对「黑箱」系统的信任度仍然很低。人工智慧工具与临床常规流程的不匹配降低了其可用性。这些障碍阻碍了人工智慧技术在临床第一线的应用。

新冠疫情的影响：

疫情加速了人们对生成式人工智慧的兴趣，因为医疗系统面临资源限制和数据缺口。人工智慧被用于模拟疾病传播、产生合成数据集以及支援远距离诊断。紧急应用案例检验了生成模型的速度和适应性。医疗机构在疫情高峰期采用人工智慧来管理文件、分诊和病患沟通。后疫情时代的策略正日益将人工智慧纳入数位化韧性的核心要素。这种转变正在加速对生成式医疗工具的长期投资。

预计在预测期内，风险与合规管理板块将成为最大的板块。

风险与合规管理领域预计将在预测期内占据最大的市场份额，因为它在文件编制、审核准备和监管报告方面发挥关键作用。生成式人工智慧正在实现政策生成、事件摘要和合规工作流程的自动化。医院和保险公司正在利用人工智慧来检测异常情况并产生审核追踪。与管治平台的整合正在提高可追溯性和回应速度。支付方和提供方对可扩展的即时合规工具的需求正在不断增长。这些功能正在巩固该领域在企业医疗保健领域的领先地位。

预计在预测期内，金融科技平台细分市场将以最高的复合年增长率成长。

预计在预测期内，金融科技平台领域将呈现最高的成长率，因为数位医疗融资和保险模式正在采用生成式人工智慧（AI）。人工智慧能够产生个人化的保险范围摘要、诈骗侦测报告和理赔说明。新兴企业正在将生成式工具整合到健康钱包和福利导航应用程式中。与应用程式介面（API）和开放银行系统的整合正在扩展其功能。各个年龄层和不同人群对医疗融资透明度和自动化的需求都在增加。

比最大的地区

在预测期内，北美预计将占据最大的市场份额，这主要得益于其先进的医疗基础设施、人工智慧投资以及监管方面的积极参与。美国正在推动生成式人工智慧在医院、保险公司和研究机构的普及。对云端平台和资料互通性的投资正在推动部署。主要人工智慧供应商和学术中心的存在正在增强创新能力。法律规范也在不断发展，以支援在临床环境中负责任地使用人工智慧。这些因素共同推动了该地区在生成式医疗应用领域的领先地位。亚太地区面临哪些挑战？

复合年增长率最高的地区：

预计亚太地区在预测期内将呈现最高的复合年增长率，这主要得益于医疗数位化、人工智慧投资和政策支援的共同推动。印度、中国、日本和韩国等国家正将生成式人工智慧应用于诊断、保险和临床研究等领域。本土新兴企业正在推出多语言工具，以满足当地医疗系统和患者的需求。各国政府正在资助公立医院和医学教育的人工智慧应用。都市区和农村医疗机构对可扩展、低成本自动化解决方案的需求日益增长。

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  • 公司简介
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    • 基于产品系列、地域覆盖和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 引言

  • 概述
  • 相关利益者
  • 分析范围
  • 分析方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 分析方法
  • 分析材料
    • 原始研究资料
    • 二手研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 介绍
  • 司机
  • 抑制因素
  • 市场机会
  • 威胁
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的感染疾病

第四章 波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代产品的威胁
  • 新参与企业的威胁
  • 公司间的竞争

5. 全球医疗保健领域生成式人工智慧市场（按解决方案类型划分）

  • 风险与合规管理
  • 自动化监管报告
  • 身份验证和KYC
  • 反洗钱 (AML) 解决方案
  • 交易监控
  • 诈欺检测与预防
  • 资料管治与隐私管理
  • 审核追踪和记录保存
  • 其他解决方案类型

6. 全球医疗保健领域生成式人工智慧市场（按监管领域划分）

  • 金融服务合规
  • 资料保护与隐私（GDPR、CCPA 等）
  • 税务和会计合规
  • 环境、社会与管治（ESG）
  • 其他监管领域

7. 全球医疗保健领域生成式人工智慧市场（以部署方式划分）

  • 云端基础的
  • 本地部署
  • 杂交种

8. 全球医疗保健领域生成式人工智慧市场（按组织规模划分）

  • 小型企业
  • 大公司

9. 全球医疗保健领域生成式人工智慧市场（按最终用户划分）

  • 银行和金融机构
  • 保险公司
  • 金融科技平台
  • 律师事务所和顾问公司
  • 医疗保健提供者
  • 其他最终用户

第十章：全球医疗保健领域生成式人工智慧市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章：主要趋势

  • 合约、商业伙伴关係和合资企业
  • 企业合併（M&A）
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十二章：公司简介

  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • Amazon Web Services, Inc.
  • NVIDIA Corporation
  • Oracle Corporation
  • Salesforce, Inc.
  • Tempus Labs, Inc.
  • Insilico Medicine, Inc.
  • PathAI, Inc.
  • Suki AI, Inc.
  • Athelas, Inc.
  • K Health, Inc.
  • Hippocratic AI, Inc.
  • Corti.ai ApS
Product Code: SMRC31813

According to Stratistics MRC, the Global Generative AI in Healthcare Market is accounted for $2.8 billion in 2025 and is expected to reach $20.1 billion by 2032 growing at a CAGR of 32.1% during the forecast period. Generative AI in healthcare refers to advanced artificial intelligence systems that create new content, insights, or solutions by learning patterns from vast medical data. These AI models can generate synthetic medical images, simulate patient outcomes, design personalized treatment plans, and assist in drug discovery. By analyzing electronic health records, genomics, and clinical research, generative AI supports predictive diagnostics, precision medicine, and medical education. Its capabilities enhance decision-making, accelerate research, and reduce costs, while ensuring improved patient care and innovation across the healthcare ecosystem.

Market Dynamics:

Driver:

Operational efficiency and cost reduction

Hospitals and insurers are deploying AI to automate documentation, streamline diagnostics, and reduce administrative overhead. Generative models are improving clinical decision support and patient engagement through synthetic data and personalized content. Integration with EHRs and workflow tools is enhancing usability and speed. Providers are using AI to optimize resource allocation and reduce burnout. These efficiencies are propelling large-scale implementation across care delivery.

Restraint:

Bias and fairness issues

Models trained on non-representative datasets can produce skewed outputs that affect diagnosis and treatment. Lack of transparency in model logic complicates validation and oversight. Disparities in outcomes may reinforce systemic inequities across patient populations. Developers face scrutiny from regulators and ethics boards. These risks continue to constrain adoption in high-stakes applications.

Opportunity:

Advancements in clinical trials

AI is generating synthetic control arms and simulating trial outcomes to reduce time and cost. Natural language models are automating protocol design and eligibility screening. Integration with real-world data is improving trial diversity and predictive accuracy. Sponsors are using AI to optimize site selection and patient engagement. These innovations are fostering transformation in clinical research.

Threat:

Resistance to adoption among healthcare professionals

Concerns about accuracy, liability, and job displacement are slowing acceptance. Many clinicians lack training to interpret or validate AI-generated outputs. Trust in black-box systems remains low without explainability and oversight. Misalignment between AI tools and clinical routines reduces usability. These barriers continue to hamper frontline adoption.

Covid-19 Impact:

The pandemic accelerated interest in generative AI as healthcare systems faced resource constraints and data gaps. AI was used to simulate disease spread, generate synthetic datasets, and support remote diagnostics. Emergency use cases validated the speed and adaptability of generative models. Providers adopted AI to manage documentation, triage, and patient communication during surges. Post-pandemic strategies now include AI as a core component of digital resilience. These shifts are accelerating long-term investment in generative healthcare tools.

The risk & compliance management segment is expected to be the largest during the forecast period

The risk & compliance management segment is expected to account for the largest market share during the forecast period due to its critical role in documentation, audit readiness, and regulatory reporting. Generative AI is automating policy generation, incident summaries, and compliance workflows. Hospitals and insurers are using AI to detect anomalies and generate audit trails. Integration with governance platforms is improving traceability and response time. Demand for scalable, real-time compliance tools is rising across payers and providers. These capabilities are boosting segment dominance in enterprise healthcare.

The fintech platforms segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the fintech platforms segment is predicted to witness the highest growth rate as digital health financing and insurance models adopt generative AI. AI is generating personalized coverage summaries, fraud detection narratives, and claims explanations. Startups are embedding generative tools into health wallets and benefit navigation apps. Integration with APIs and open banking systems is expanding functionality. Demand for transparency and automation in health finance is rising across demographics.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its advanced healthcare infrastructure, AI investment, and regulatory engagement. The United States is scaling generative AI across hospitals, insurers, and research institutions. Investment in cloud platforms and data interoperability is driving deployment. Presence of leading AI vendors and academic centers is reinforcing innovation. Regulatory frameworks are evolving to support responsible AI in clinical settings. These factors are boosting regional leadership in generative healthcare applications. Matter for Asia Pacific?

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR as healthcare digitization, AI investment, and policy support converge. Countries like India, China, Japan, and South Korea are scaling generative AI across diagnostics, insurance, and clinical research. Local startups are launching multilingual tools tailored to regional health systems and patient needs. Governments are funding AI integration in public hospitals and medical education. Demand for scalable, low-cost automation is rising across urban and rural care settings.

Key players in the market

Some of the key players in Generative AI in Healthcare Market include IBM Corporation, Microsoft Corporation, Google LLC, Amazon Web Services, Inc., NVIDIA Corporation, Oracle Corporation, Salesforce, Inc., Tempus Labs, Inc., Insilico Medicine, Inc., PathAI, Inc., Suki AI, Inc., Athelas, Inc., K Health, Inc., Hippocratic AI, Inc. and Corti.ai ApS.

Key Developments:

In May 2025, Microsoft deepened its healthcare partnerships through Microsoft Cloud for Healthcare, integrating generative AI into clinical documentation, diagnostics, and patient engagement. Collaborations with Epic Systems and Nuance enabled real-time chart summarization and ambient clinical intelligence, helping reduce physician burnout and improve care delivery.

In December 2024, IBM announced expanded partnerships across its AI Ecosystem, enabling healthcare enterprises to move generative AI projects from pilot to production. These collaborations focus on responsible scaling, integrating IBM's enterprise-grade AI with partner expertise to modernize diagnostics, patient engagement, and clinical workflows.

Solution Types Covered:

  • Risk & Compliance Management
  • Regulatory Reporting Automation
  • Identity Verification & KYC
  • Anti-Money Laundering (AML) Solutions
  • Transaction Monitoring
  • Fraud Detection & Prevention
  • Data Governance & Privacy Management
  • Audit Trail & Recordkeeping
  • Other Solution Types

Regulatory Domain s Covered:

  • Financial Services Compliance
  • Data Protection & Privacy (GDPR, CCPA, etc.)
  • Tax & Accounting Compliance
  • Environmental, Social & Governance (ESG)
  • Other Regulatory Domains

Deployment Modes Covered:

  • Cloud-Based
  • On-Premise
  • Hybrid

Organization Sizes Covered:

  • Small & Medium Enterprises (SMEs)
  • Large Enterprises

End Users Covered:

  • Banks & Financial Institutions
  • Insurance Companies
  • Fintech Platforms
  • Legal & Consulting Firms
  • Healthcare Providers
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 End User Analysis
  • 3.7 Emerging Markets
  • 3.8 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Generative AI in Healthcare Market, By Solution Type

  • 5.1 Introduction
  • 5.2 Risk & Compliance Management
  • 5.3 Regulatory Reporting Automation
  • 5.4 Identity Verification & KYC
  • 5.5 Anti-Money Laundering (AML) Solutions
  • 5.6 Transaction Monitoring
  • 5.7 Fraud Detection & Prevention
  • 5.8 Data Governance & Privacy Management
  • 5.9 Audit Trail & Recordkeeping
  • 5.10 Other Solution Types

6 Global Generative AI in Healthcare Market, By Regulatory Domain

  • 6.1 Introduction
  • 6.2 Financial Services Compliance
  • 6.3 Data Protection & Privacy (GDPR, CCPA, etc.)
  • 6.4 Tax & Accounting Compliance
  • 6.5 Environmental, Social & Governance (ESG)
  • 6.6 Other Regulatory Domains

7 Global Generative AI in Healthcare Market, By Deployment Mode

  • 7.1 Introduction
  • 7.2 Cloud-Based
  • 7.3 On-Premise
  • 7.4 Hybrid

8 Global Generative AI in Healthcare Market, By Organization Size

  • 8.1 Introduction
  • 8.2 Small & Medium Enterprises (SMEs)
  • 8.3 Large Enterprises

9 Global Generative AI in Healthcare Market, By End User

  • 9.1 Introduction
  • 9.2 Banks & Financial Institutions
  • 9.3 Insurance Companies
  • 9.4 Fintech Platforms
  • 9.5 Legal & Consulting Firms
  • 9.6 Healthcare Providers
  • 9.7 Other End Users

10 Global Generative AI in Healthcare Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 IBM Corporation
  • 12.2 Microsoft Corporation
  • 12.3 Google LLC
  • 12.4 Amazon Web Services, Inc.
  • 12.5 NVIDIA Corporation
  • 12.6 Oracle Corporation
  • 12.7 Salesforce, Inc.
  • 12.8 Tempus Labs, Inc.
  • 12.9 Insilico Medicine, Inc.
  • 12.10 PathAI, Inc.
  • 12.11 Suki AI, Inc.
  • 12.12 Athelas, Inc.
  • 12.13 K Health, Inc.
  • 12.14 Hippocratic AI, Inc.
  • 12.15 Corti.ai ApS

List of Tables

  • Table 1 Global Generative AI in Healthcare Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Generative AI in Healthcare Market Outlook, By Solution Type (2024-2032) ($MN)
  • Table 3 Global Generative AI in Healthcare Market Outlook, By Risk & Compliance Management (2024-2032) ($MN)
  • Table 4 Global Generative AI in Healthcare Market Outlook, By Regulatory Reporting Automation (2024-2032) ($MN)
  • Table 5 Global Generative AI in Healthcare Market Outlook, By Identity Verification & KYC (2024-2032) ($MN)
  • Table 6 Global Generative AI in Healthcare Market Outlook, By Anti-Money Laundering (AML) Solutions (2024-2032) ($MN)
  • Table 7 Global Generative AI in Healthcare Market Outlook, By Transaction Monitoring (2024-2032) ($MN)
  • Table 8 Global Generative AI in Healthcare Market Outlook, By Fraud Detection & Prevention (2024-2032) ($MN)
  • Table 9 Global Generative AI in Healthcare Market Outlook, By Data Governance & Privacy Management (2024-2032) ($MN)
  • Table 10 Global Generative AI in Healthcare Market Outlook, By Audit Trail & Recordkeeping (2024-2032) ($MN)
  • Table 11 Global Generative AI in Healthcare Market Outlook, By Other Solution Types (2024-2032) ($MN)
  • Table 12 Global Generative AI in Healthcare Market Outlook, By Regulatory Domain (2024-2032) ($MN)
  • Table 13 Global Generative AI in Healthcare Market Outlook, By Financial Services Compliance (2024-2032) ($MN)
  • Table 14 Global Generative AI in Healthcare Market Outlook, By Data Protection & Privacy (GDPR, CCPA, etc.) (2024-2032) ($MN)
  • Table 15 Global Generative AI in Healthcare Market Outlook, By Tax & Accounting Compliance (2024-2032) ($MN)
  • Table 16 Global Generative AI in Healthcare Market Outlook, By Environmental, Social & Governance (ESG) (2024-2032) ($MN)
  • Table 17 Global Generative AI in Healthcare Market Outlook, By Other Regulatory Domains (2024-2032) ($MN)
  • Table 18 Global Generative AI in Healthcare Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 19 Global Generative AI in Healthcare Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 20 Global Generative AI in Healthcare Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 21 Global Generative AI in Healthcare Market Outlook, By Hybrid (2024-2032) ($MN)
  • Table 22 Global Generative AI in Healthcare Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 23 Global Generative AI in Healthcare Market Outlook, By Small & Medium Enterprises (SMEs) (2024-2032) ($MN)
  • Table 24 Global Generative AI in Healthcare Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 25 Global Generative AI in Healthcare Market Outlook, By End User (2024-2032) ($MN)
  • Table 26 Global Generative AI in Healthcare Market Outlook, By Banks & Financial Institutions (2024-2032) ($MN)
  • Table 27 Global Generative AI in Healthcare Market Outlook, By Insurance Companies (2024-2032) ($MN)
  • Table 28 Global Generative AI in Healthcare Market Outlook, By Fintech Platforms (2024-2032) ($MN)
  • Table 29 Global Generative AI in Healthcare Market Outlook, By Legal & Consulting Firms (2024-2032) ($MN)
  • Table 30 Global Generative AI in Healthcare Market Outlook, By Healthcare Providers (2024-2032) ($MN)
  • Table 31 Global Generative AI in Healthcare Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.