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1856949

全球醫療保健領域生成式人工智慧市場：預測至 2032 年—按解決方案類型、監管領域、部署方式、組織規模、最終用戶和地區進行分析

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個工作天內

價格

根據 Stratistics MRC 的數據，預計 2025 年全球醫療保健領域的生成式人工智慧市場規模將達到 28 億美元，到 2032 年將達到 201 億美元，預測期內複合年成長率將達到 32.1%。

醫療保健領域的生成式人工智慧是指利用先進的人工智慧系統，透過學習大量醫療數據中的模式，創造新的內容、洞見或解決方案。這些人工智慧模型可以產生合成醫學影像、模擬患者預後、設計個人化治療方案，並輔助藥物研發。透過分析電子健康記錄、基因組學和臨床研究，生成式人工智慧能夠支援預測性診斷、精準醫療和醫學教育。其功能可增強決策能力、加速研究、降低成本，並促進整個醫療保健生態系統中患者照護和創新的提升。

提高營運效率和降低成本

醫院和保險公司正在採用人工智慧來實現文件自動化、簡化診斷流程並降低行政成本。生成模型透過合成數據和個人化內容，正在改善臨床決策支援和病人參與。與電子病歷和工作流程工具的整合正在提高可用性和速度。醫療保健專業人員正在利用人工智慧來最佳化資源分配並減少職業倦怠。這些效率提升正在推動人工智慧在醫療保健領域的廣泛應用。

偏見和公平性問題

基於非代表性資料集訓練的模型可能會產生扭曲的輸出結果，進而影響診斷和治療。模型邏輯缺乏透明度會使檢驗和監督變得複雜。結果差異可能會加劇患者群體中存在的系統性不平等。開發者也面臨監管機構和倫理委員會的審查。這些風險持續限制高風險應用的普及。

臨床試驗進展

人工智慧正在產生合成對照組並模擬試驗結果，以減少時間和成本。自然語言模型正在實現方案設計和合格篩檢的自動化。與真實數據的整合正在提高試驗的多樣性和預測準確性。申辦方正在利用人工智慧最佳化研究中心的選擇和病人參與。這些創新正在推動臨床研究的變革。

不願聘用醫療專業人員

對準確性、責任歸屬和人員流動等方面的擔憂正在減緩人工智慧技術的普及。許多臨床醫生沒有接受過解讀和檢驗人工智慧產生結果的培訓。由於缺乏可解釋性和監督機制，人們對「黑箱」系統的信任度仍然很低。人工智慧工具與臨床常規流程的不匹配降低了其可用性。這些障礙阻礙了人工智慧技術在臨床第一線的應用。

新冠疫情的影響：

疫情加速了人們對生成式人工智慧的興趣，因為醫療系統面臨資源限制和數據缺口。人工智慧被用於模擬疾病傳播、產生合成資料集以及支援遠距離診斷。緊急應用案例檢驗了生成模型的速度和適應性。醫療機構在疫情高峰期採用人工智慧來管理文件、分診和病患溝通。後疫情時代的策略正日益將人工智慧納入數位化韌性的核心要素。這種轉變正在加速對生成式醫療工具的長期投資。

預計在預測期內，風險與合規管理板塊將成為最大的板塊。

風險與合規管理領域預計將在預測期內佔據最大的市場佔有率，因為它在文件編制、審核準備和監管報告方面發揮關鍵作用。生成式人工智慧正在實現政策生成、事件摘要和合規工作流程的自動化。醫院和保險公司正在利用人工智慧來檢測異常情況並產生審核追蹤。與管治平台的整合正在提高可追溯性和回應速度。支付方和提供方對可擴展的即時合規工具的需求正在不斷成長。這些功能正在鞏固該領域在企業醫療保健領域的領先地位。

預計在預測期內，金融科技平台細分市場將以最高的複合年成長率成長。

預計在預測期內，金融科技平台領域將呈現最高的成長率，因為數位醫療融資和保險模式正在採用生成式人工智慧（AI）。人工智慧能夠產生個人化的保險範圍摘要、詐騙偵測報告和理賠說明。新興企業正在將生成式工具整合到健康錢包和福利導航應用程式中。與應用程式介面（API）和開放銀行系統的整合正在擴展其功能。各個年齡層和不同人群對醫療融資透明度和自動化的需求都在增加。

比最大的地區

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其先進的醫療基礎設施、人工智慧投資以及監管方面的積極參與。美國正在推動生成式人工智慧在醫院、保險公司和研究機構的普及。對雲端平台和資料互通性的投資正在推動部署。主要人工智慧供應商和學術中心的存在正在增強創新能力。法律規範也在不斷發展，以支援在臨床環境中負責任地使用人工智慧。這些因素共同推動了該地區在生成式醫療應用領域的領先地位。亞太地區面臨哪些挑戰？

複合年成長率最高的地區：

預計亞太地區在預測期內將呈現最高的複合年成長率，這主要得益於醫療數位化、人工智慧投資和政策支援的共同推動。印度、中國、日本和韓國等國家正將生成式人工智慧應用於診斷、保險和臨床研究等領域。本土新興企業正在推出多語言工具，以滿足當地醫療系統和患者的需求。各國政府正在資助公立醫院和醫學教育的人工智慧應用。都市區和農村醫療機構對可擴展、低成本自動化解決方案的需求日益成長。

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    • 根據客戶興趣對主要國家進行市場估算、預測和複合年成長率分析（註：基於可行性檢查）
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    • 基於產品系列、地域覆蓋和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 分析方法
  • 分析材料
    • 原始研究資料
    • 二手研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 介紹
  • 促進要素
  • 抑制因素
  • 市場機遇
  • 威脅
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的感染疾病

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代產品的威脅
  • 新參與企業的威脅
  • 公司間的競爭

5. 全球醫療保健領域生成式人工智慧市場（按解決方案類型分類）

  • 風險與合規管理
  • 自動化監管報告
  • 身份驗證和KYC
  • 反洗錢 (AML) 解決方案
  • 交易監控
  • 詐欺檢測與預防
  • 資料管治與隱私管理
  • 審核追蹤和記錄保存
  • 其他解決方案類型

6. 全球醫療保健領域生成式人工智慧市場（按監管領域分類）

  • 金融服務合規
  • 資料保護與隱私（GDPR、CCPA 等）
  • 稅務和會計合規
  • 環境、社會與管治（ESG）
  • 其他監管領域

7. 全球醫療保健領域生成式人工智慧市場（以部署方式分類）

  • 雲端基礎的
  • 本地部署
  • 混合

8. 全球醫療保健領域生成式人工智慧市場（按組織規模分類）

  • 小型企業
  • 主要企業

9. 全球醫療保健領域生成式人工智慧市場（按最終用戶分類）

  • 銀行和金融機構
  • 保險公司
  • 金融科技平台
  • 律師事務所和顧問公司
  • 醫療保健提供者
  • 其他最終用戶

第10章：全球醫療保健領域生成式人工智慧市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章：主要趨勢

  • 合約、商業夥伴關係和合資企業
  • 企業合併（M&A）
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第12章：公司簡介

  • 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.