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1817405

醫療保健的生成AI市場:2035年前的產業趨勢和全球預測 - 各目的，各報價環類型，各應用領域，各終端用戶，各主要地區，主要加入企業

Generative AI in Healthcare Market: Industry Trends and Global Forecasts, Till 2035 - Distribution by Purpose, Type of Offering, Application Area, End-User, Key Geographical Regions and Leading Players:
出版日期: | 出版商: Roots Analysis | 英文 210 Pages | 商品交期: 最快1-2個工作天內

價格

醫療保健生成式人工智慧市場概覽

全球醫療保健生成式人工智慧市場目前估值 33 億美元，預計在預測期內將以 28% 的複合年增長率成長，到 2035 年將達到 398 億美元。

醫療保健生成式人工智慧市場機會細分為以下幾個部分：

目的

  • 臨床為基礎的目的
  • 系統為基礎的目的

報價環類型

  • 科技/平台
  • 服務

應用領域

  • 藥物研發與開發
  • 診斷
  • 治療
  • 管理業務
  • 其他

終端用戶

  • 製藥公司及生命科學企業
  • 醫療保健供應商
  • 其他的終端用戶

主要地區

  • 北美
  • 歐洲
  • 亞太地區
  • 中東·北非
  • 南美

北美市場

  • 美國
  • 加拿大

歐洲市場

  • 德國
  • 英國
  • 法國
  • 西班牙
  • 瑞士
  • 荷蘭
  • 其他歐洲

亞太地區市場

  • 中國
  • 日本
  • 韓國
  • 新加坡
  • 印度
  • 其他

中東·北非市場

  • 以色列
  • 阿拉伯聯合大公國
  • 其他

南美市場

  • 巴西
  • 其他

醫療保健市場中的生成式人工智慧成長與趨勢

生成式人工智慧是人工智慧的一個分支，它利用生成模型創建資料驅動的輸出，例如洞察、圖像、視訊和其他格式。在醫療保健領域，這項技術正在迅速發展，並有可能改變病患照護、研究和治療方式。

醫療保健產業目前正面臨許多課題，錯綜複雜，包括臨床工作流程效率低、治療成本上升、人員短缺以及醫護人員倦怠。根據 Medscape 發布的 "2024 年醫生倦怠與憂鬱報告" ，約 49% 的醫生表示經歷過倦怠，其中包括行政負擔（62%）和長時間工作（41%）。此外，傳統的藥物研發方法缺乏對個人化治療方案的關注，並且仍然耗時且耗力。此外，儘管投入了大量的時間和金錢，但仍有約 90% 的新藥候選藥物未能進入臨床試驗階段。如此高的失敗率不僅扼殺了創新，也增加了全球醫療保健系統的財務負擔。

為了應對這些課題，一些製藥和生命科學公司對採用生成式人工智慧 (CGAI) 的興趣日益濃厚。此外，值得強調的是，醫療產業的生成性人工智慧在自動化行政流程以提高整體營運效率、透過高階成像提高診斷準確性、個人化患者參與以及加速藥物發現和開發方面具有巨大潛力。具體而言，僅在行政營運中實施生成性人工智慧就可以為整個醫療產業節省約1500億美元。此外，研究表明，生成性人工智慧可以將診斷錯誤減少高達85%，將護理師加班時間減少21%，從而在三年內為每家醫院節省約469,000美元的潛在成本。然而，隨著醫療機構將生成性人工智慧整合到其系統中，建立一個強大的治理框架至關重要，以確保人工智慧的道德使用並解決資料隱私、演算法偏差和透明度等關鍵問題。

醫療健康市場中的生成式人工智慧-IMG1

近年來，多家製藥和醫療保健公司與多家人工智慧公司建立了策略合作夥伴關係，共同探索生成式人工智慧在醫療保健領域的應用。同時，多家生成式人工智慧開發公司已獲得大量資金，以增強其針對各種醫療應用的模型能力。鑑於投資者興趣日益增長以及合作環境不斷擴大，醫療健康領域的生成式人工智慧市場預計將在未來幾年持續成長。

醫療健康領域的生成式人工智慧市場：關鍵洞察

本報告深入探討了醫療健康領域生成式人工智慧市場的現狀，並揭示了該行業的潛在成長機會。報告的主要內容包括：

  • 在醫療保健產業提供生成式人工智慧解決方案的公司中，超過 45% 為中型企業，其中 79% 總部位於北美。
  • 超過 85% 的公司提供生成式人工智慧技術/平台，以簡化各種醫療保健流程，27% 的生成式人工智慧公司能夠滿足醫療保健提供者和 P/B 公司不斷變化的需求。
  • 人們對該領域日益增長的興趣也體現在合作活動的增多，近 90% 的交易是在過去兩年內達成的。
醫療保健市場中的生成式人工智慧-IMG2
  • 我們的分析預測，買方在生成式人工智慧醫療保健市場的議價能力非常高。
  • 醫療保健領域行政負擔的增加、資金和投資的增加以及人工智慧和機器學習的進步預計將推動醫療保健領域生成式人工智慧市場的發展，並在可預見的未來實現穩步增長。
  • 技術/平台部分目前佔近 75% 的市場。預計到2035年，醫療保健領域的生成式人工智慧市場將以28%的複合年增長率持續成長。
醫療保健領域的生成式人工智慧市場-IMG3

醫療保健領域的生成式人工智慧市場：主要細分市場

依用途劃分，全球市場分為基於臨床用途及基於系統用途兩大類。其中，基於臨床用途的細分市場目前佔了整個市場的最大佔有率。這可能是因為醫療保健領域的生成式人工智慧能夠幫助臨床醫生做出更明智的決策，並且在醫院和診所的應用日益廣泛，直接影響患者護理。

依產品類型劃分，全球醫療保健領域的生成式人工智慧市場分為平台/技術和服務。目前，平台/技術部門佔了整個市場的最大佔有率。然而，值得注意的是，服務部門預計在預測期內將以相對較高的複合年增長率成長。

依應用領域劃分，全球醫療保健生成式人工智慧市場分為藥物研發和市場推廣、診斷、治療、行政營運和其他應用。目前，治療領域在醫療保健生成式人工智慧市場中處於領先地位。需要強調的是，這一趨勢未來不太可能改變。這是因為生成式人工智慧可以改善治療效果和患者護理，減輕行政負擔，並促進臨床應用的持續成長。

按最終用戶劃分，全球醫療保健生成式人工智慧市場分為製藥和生命科學公司、醫療保健提供者和其他最終用戶。目前，該市場主要由供醫療保健提供者使用的系統產生的收入主導。此外，由於基因人工智慧解決方案的廣泛應用，包括增強患者護理、提高營運效率、數據驅動的洞察以及潛在的成本節約，這一市場趨勢未來不太可能改變。

依主要地區劃分，市場分為北美、歐洲、亞太、中東和北非以及拉丁美洲。在當前情況下，北美很可能佔最大的市場佔有率。此外，值得注意的是，預計亞太地區在預測期內將以相對較高的複合年增長率成長。

醫療保健的生成AI市場參與企業案例

  • Amazon Web Services
  • C3 AI
  • Exscientia
  • Google
  • Huma
  • IBM
  • Iktos
  • LeewayHertz
  • Medical IP
  • Microsoft
  • NVIDIA
  • OpenAI
  • Oracle
  • PhamaX
  • Syntegra

初步研究概要

本研究中提出的觀點和見解受到與多位利害關係人討論的影響。本研究報告包含與以下產業參與者的詳細訪談記錄：

  • 一家美國中型公司的財務副總裁兼投資者關係主管
  • 一家以色列中型公司的行銷總監
  • 一家法國中型公司的亞洲應用科學家

醫療保健領域生成式人工智慧市場研究報告

本報告研究了醫療保健領域生成式人工智慧市場，並得出以下結論：

  • 市場規模和機會分析：本報告深入分析了醫療保健領域生成式人工智慧市場的當前市場機會和未來成長潛力，重點關注關鍵細分市場，例如[A] 目標、[B] 交付類型、[C] 應用領域、[D] 最終用戶、[E] 主要地區和[G] 關鍵參與者。
  • 市場影響分析：對可能影響市場成長的各種因素進行全面分析，包括[A]推動因素、[B]阻礙因素、[C]機會和[D]現有課題。
  • 市場格局：本報告基於若干相關參數，對醫療保健提供者中的生成性人工智慧進行了全面評估，包括[A]交付類型、[B]應用領域和[C]最終用戶。
  • 醫療保健提供者中的生成性人工智慧展望：列出在此領域運營的醫療保健提供者中的生成性人工智慧公司，並基於[A]成立年份、[B]公司規模、[C]總部位置和[D]生成性人工智慧公司類型進行分析。
  • 競爭分析：基於各種相關參數，例如[A]公司優勢、[B]服務組合優勢等。基於市場佔有率，對醫療領域生成式人工智慧提供者進行深入的競爭分析。
  • 公司簡介：包含以下資訊：A) 公司概況、[B] 財務資訊（如有）、[C] 醫療領域生成式人工智慧產品組合、[D] 近期發展和 [E] 未來展望。
  • 合作夥伴關係與合作：基於若干相關參數，對醫療領域生成式人工智慧市場利益相關者之間達成的合作夥伴關係進行詳細分析，例如 A) 合作年份、[B] 合作類型、[C] 合作公司類型、[D] 合作目標、[E] 地區和 [G] 最活躍的參與者（合作夥伴數量）。
  • 醫療領域生成式人工智慧用例：醫療領域生成式人工智慧用例的詳細案例研究，介紹醫療領域各生成式人工智慧公司之間達成的合作資訊。每個用例都提供有關各種參數的信息，例如 [A] 參與公司概況、[B] 業務需求、[C] 已實現目標的詳細資訊以及 [D] 提供的解決方案。

目錄

章節1 報告概要

第1章 序文

第2章 調查手法

第3章 市場動態

  • 章概要
  • 預測調查手法
  • 市場評估組成架構
  • 預測工具和技巧
  • 重要的考慮事項
  • 限制事項

第4章 宏觀經濟指標

  • 章概要
  • 市場動態
  • 結論

章節2 定性洞察

第5章 摘要整理

第6章 簡介

章節3 場概要

第7章 競爭情形

  • 章概要
  • 醫療保健的生成AI企業:市場形勢

第8章 企業競爭力分析

  • 章概要
  • 前提主要的參數
  • 調查手法
  • 醫療保健的生成AI企業:企業競爭力分析

章節4 企業簡介

第9章 北美的醫療保健的生成AI企業

  • 章概要
  • 北美設置據點的生成AI企業的詳細介紹
    • IBM
    • Microsoft
    • NVIDIA
    • OpenAI
  • 北美設置據點的生成AI企業的簡介
    • Amazon Web Services
    • C3 AI
    • Google
    • Oracle
    • Syntegra

第10章 歐洲和亞太地區的醫療保健的生成AI企業

  • 章概要
  • 在歐洲和亞太地區設置據點的生成AI企業的詳細介紹
    • Huma
    • LeewayHertz
  • 在歐洲和亞太地區設置據點的生成AI企業的簡介
    • Exscientia
    • Iktos
    • Medical IP
    • PhamaX

章節5 市場趨勢

第11章 夥伴關係和合作

第12章 醫療保健的生成AI:使用案例

  • 章概要
  • 使用案例1:NVIDIA和Genentech的合作
  • 使用案例2:Insilico Medicine和Inimmune的合作
  • 使用案例3:OpenAI和Moderna的合作
  • 使用案例4:Amazon Web Services和Pfizer的合作
  • 使用案例5:Suki和Ascension Saint Thomas的合作
  • 使用案例6:Abridge和Emory Healthcare的合作
  • 使用案例7:Google和China Medical University Hospital的聯合

章節6 市場機會分析

第13章 市場影響分析:促進因素，阻礙因素，機會，課題

第14章 醫療保健市場上全球的生成AI

第15章 醫療保健市場上生成AI(各目的)

第16章 醫療保健市場上生成AI(各提供類型)

第17章 醫療保健市場上生成AI(各應用領域)

第18章 醫療保健市場上生成AI(各終端用戶)

第19章 醫療保健市場上生成AI(各地區)

第20章 醫療保健市場上生成AI(主要加入企業)

第21章 鄰近市場分析

章節7 策略工具

第22章 波特的五力分析

章節8 其他獨家洞察

第23章 來自初步研究的洞察

第24章 結論

章節9 附錄

第25章 表格形式資料

第26章 企業·團體一覽

第27章 客制化的機會

第28章 始祖訂閱服務

第29章 著者詳細內容

Product Code: RA100521

GENERATIVE AI in HEALTHCARE MARKET: OVERVIEW

As per Roots Analysis, the global generative AI in healthcare market is currently valued at USD 3.3 billion and is projected to reach USD 39.8 billion by 2035, growing at a CAGR of 28% during the forecast period.

The opportunity for generative AI in healthcare market has been distributed across the following segments:

Purpose

  • Clinical-based Purpose
  • System-based Purpose

Type of Offering

  • Technology / Platform
  • Service

Application Area

  • Drug Discovery and Development
  • Diagnosis
  • Treatment
  • Administrative Tasks
  • Other Application Areas

End-User

  • Pharmaceutical and Life Science Companies
  • Healthcare Providers
  • Other End-Users

Key Geographical Regions

  • North America
  • Europe
  • Asia-Pacific
  • Middle East and North Africa
  • Latin America

Market in North America

  • US
  • Canada

Market in Europe

  • Germany
  • UK
  • France
  • Spain
  • Switzerland
  • The Netherlands
  • Rest of Europe

Market in Asia-Pacific

  • China
  • Japan
  • South Korea
  • Singapore
  • India
  • Rest of Asia-Pacific

Market in Middle East and North Africa

  • Israel
  • UAE
  • Rest of Middle East and North Africa

Market in Latin America

  • Brazil
  • Rest of Latin America

Generative AI in Healthcare Market: Growth and Trends

Generative AI is a part of artificial intelligence that utilizes generative models to create data-driven outputs, such as insights, images, videos, and other formats. In the healthcare sector, this technology is evolving rapidly, with the potential to transform patient care, research and treatment.

The healthcare industry is currently navigating a complex landscape marked by a number of challenges, including inefficiencies in clinical workflows, escalating treatment costs, staff shortages, and burnout of the healthcare workers. According to Medscape's 2024 Physician Burnout and Depression Report, nearly 49% of physicians reported feeling burnt out, with administrative burdens (62%) and long working hours (41%). In addition, the conventional drug discovery methods remain time-intensive with no focus on the personalized treatment approaches. Moreover, about 90% of drug candidates fail to progress to advanced clinical trial phases, despite significant time and financial investments. This high failure rate not only impedes innovation but also intensifies the financial strains on the global healthcare systems.

To address these challenges, several pharmaceutical and life sciences companies have increasingly shown interest in exploring the adoption of generative AI. Further, it is important to highlight that generative AI in healthcare industry holds great potential in automating administrative processes for improving the overall operational efficiency, enhancing diagnostic accuracy through advanced imaging, personalizing patient engagement, and accelerating drug discovery and development. Notably, the implementation of generative AI in administrative tasks alone could generate annual savings of approximately USD 150 billion across the healthcare sector. Additionally, studies suggest generative AI could reduce diagnostic errors by up to 85% and reduce nursing overtime by 21%, resulting in potential cost savings of nearly USD 469,000 over the span of three years per hospital. However, as healthcare organizations integrate generative AI into their systems, it is essential to establish robust governance frameworks that ensure ethical AI use and address key concerns, such as data privacy, algorithmic bias, and transparency.

Generative AI in Healthcare Market - IMG1

In recent years, several pharmaceutical and healthcare companies have entered into strategic partnerships with various AI firms to explore applications of generative AI in healthcare. Simultaneously, several generative AI developers are securing significant funding in order to enhance their model capabilities for diverse medical applications. Given the growing interest of the investors and the expanding collaborative landscape, generative AI in healthcare market is poised for sustained growth in the coming years.

Generative AI in Healthcare Market: Key Insights

The report delves into the current state of the generative AI in healthcare market and identifies potential growth opportunities within industry. The key takeaways of the report are:

  • More than 45% of the companies engaged in offering generative AI solutions in the healthcare industry are mid-sized firms; of these, 79% of the firms are headquartered in North America.
  • >85% of the companies offer gen AI technology / platforms to streamline various healthcare processes; of these, 27% of the gen AI companies cater to the evolving needs of both, healthcare providers and P / B companies.
  • The rising interest in this domain is reflected by the rise in partnership activity; notably, close to 90% of the deals were inked in the last two years.
Generative AI in Healthcare Market - IMG2
  • Based on our analysis, in the generative AI in healthcare market, we expect the buyers to have a very high bargaining power; any initiative taken must be carefully evaluated, considering the likely future market dynamics.
  • The increasing administrative burden in healthcare, rising funding and investments, and advancements in AI and ML are likely to drive the market for gen AI in healthcare, leading to steady growth in the foreseeable future.
  • The technology / platform segment dominates the current market with close to 75% of the market share; notably, generative AI in healthcare market is anticipated to grow at a lucrative growth rate (CAGR of 28%) till 2035.
Generative AI in Healthcare Market - IMG3

Generative AI in Healthcare Market: Key Segments

Generative AI used for Clinical-based Purposes is Likely to Hold the Largest Share of the Current Market During the Forecast Period

Based on purpose, the global market is segmented into clinical-based and system-based purposes. Amongst these types, the clinical-based purpose segment occupies the largest share of the current overall market. This can be attributed to their direct impact on patient care, as these would help the clinicians make informed decisions, increasing their adoption in the hospitals and clinics.

Based on the Type of Offering, Platform / Technology Segment Captures the Majority of the Current Market Share

Based on the type of offerings, the global generative AI in healthcare market is segmented into platform / technology and service. Presently, the platform / technology segment occupies the highest share in the overall market. However, it is important to note that the services segment is anticipated to grow at a relatively higher CAGR during the forecast period.

Treatment Segment is Likely to Hold the Largest Share in the Generative AI in Healthcare Market During the Forecast Period

Based on the application area, the global generative AI in healthcare market is segmented into drug discovery and development, diagnosis, treatment, administrative tasks and other application areas. Currently, the treatment segment leads generative AI in healthcare market. It is important to highlight that this trend is unlikely to change in the future as well. This can be attributed to the fact that generative AI boosts treatment efficacy and patient care, reducing administrative burdens, driving sustained growth in clinical applications.

Generative AI in Healthcare Market for Healthcare Providers is Likely to Grow at a Relatively Faster Pace During the Forecast Period

Based on the end-user, the global generative AI in healthcare market is segmented across pharmaceutical and life science companies, healthcare providers and other end-users. Presently, the market is dominated by the revenues generated through the systems intended for use by healthcare providers. Further, this market trend is unlikely to change in the future as well owing to the wider applicability of the gen AI solutions, such as enhanced patient care, improved operational efficiency, data driven insights and cost saving potential.

North America Accounts for the Largest Share in the Market

Based on key geographical regions, the market is segmented into North America, Europe, Asia-Pacific, Middle East and North Africa and Latin America. In the current scenario, North America is likely to capture the largest market share. Further, it is worth highlighting that Asia-Pacific is expected to grow at a relatively high CAGR during the forecast period.

Example Players in the Generative AI in Healthcare Market

  • Amazon Web Services
  • C3 AI
  • Exscientia
  • Google
  • Huma
  • IBM
  • Iktos
  • LeewayHertz
  • Medical IP
  • Microsoft
  • NVIDIA
  • OpenAI
  • Oracle
  • PhamaX
  • Syntegra

Primary Research Overview

The opinions and insights presented in this study were influenced by discussions conducted with multiple stakeholders. The research report features detailed transcripts of interviews held with the following industry stakeholders:

  • Vice President, Finance and Head of Investor Relations, Mid-sized Company in the US
  • Marketing Director, Mid-sized Company in Israel
  • Application Scientist of Asia, Mid-sized Company in France

Generative AI in Healthcare Market: Research Coverage

The report on generative AI in healthcare market features insights into various sections, including:

  • Market Sizing and Opportunity Analysis: An in-depth analysis of current market opportunity and the future growth potential of generative AI in healthcare market, focusing on key market segments, including [A] purpose, [B] type of offering, [C] application area, [D] end-user, [E] key geographical regions, and [G] leading players.
  • Market Impact Analysis: A thorough analysis of various factors, such as [A] drivers, [B] restraints, [C] opportunities, and [D] existing challenges that are likely to impact market growth.
  • Market Landscape: A comprehensive evaluation of generative AI in healthcare providers, based on several relevant parameters, such as [A] type of offering, [B] application area, and [C] end-user.
  • Generative AI in Healthcare Providers Landscape: The report features a list of generative AI in healthcare providers engaged in this domain, along with analyses based on [A] year of establishment, [B] company size [C] location of headquarters, and [D] type of generative AI company.
  • Company Competitiveness Analysis: An insightful competitiveness analysis of the generative AI in healthcare providers, based on various relevant parameters, such as [A] company strength, and [B] service portfolio strength.
  • Company Profiles: Comprehensive profiles of key industry players in the generative AI in the healthcare domain, featuring information on [A] company overview, [B] financial information (if available), [C] generative AI in healthcare portfolio, [D] recent developments, and [E] future outlook statements.
  • Partnerships and Collaborations: A detailed analysis of partnerships inked between stakeholders in the generative AI in healthcare market, based on several relevant parameters, such as [A] year of partnership, [B] type of partnership, [C] type of partner company, [D] purpose of partnership, [E] geography, and [G] most active players (in terms of number of partnerships).
  • Generative AI in Healthcare Use Cases: A detailed case study of the use cases of generative AI in healthcare, presenting information on collaborations inked between various generative AI companies in healthcare. Each use case provides information on various parameters, such as [A] a brief overview of the companies involved, [B] business needs [C] details on the objectives achieved, and [D] solutions provided.

Key Questions Answered in this Report

  • How many companies are currently engaged in this market?
  • Which are the leading companies in this market?
  • What factors are likely to influence the evolution of this market?
  • What is the current and future market size?
  • What is the CAGR of this market?
  • How is the current and future market opportunity likely to be distributed across key market segments?

Reasons to Buy this Report

  • The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
  • Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
  • The report offers stakeholders a comprehensive overview of the market, including key drivers, barriers, opportunities, and challenges. This information empowers stakeholders to stay abreast of market trends and make data-driven decisions to capitalize on growth prospects.

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TABLE OF CONTENTS

SECTION I: REPORT OVERVIEW

1. PREFACE

  • 1.1. Introduction
  • 1.2. Market Share Insights
  • 1.3. Key Market Insights
  • 1.4. Report Coverage
  • 1.5. Key Questions Answered
  • 1.6. Chapter Outlines

2. RESEARCH METHODOLOGY

  • 2.1. Chapter Overview
  • 2.2. Research Assumptions
    • 2.2.1. Market Landscape and Market Trends
    • 2.2.2. Market Forecast and Opportunity Analysis
    • 2.2.3. Comparative Analysis
  • 2.3. Database Building
    • 2.3.1. Data Collection
    • 2.3.2. Data Validation
    • 2.3.3. Data Analysis
  • 2.4. Project Methodology
    • 2.4.1. Secondary Research
      • 2.4.1.1. Annual Reports
      • 2.4.1.2. Academic Research Papers
      • 2.4.1.3. Company Websites
      • 2.4.1.4. Investor Presentations
      • 2.4.1.5. Regulatory Filings
      • 2.4.1.6. White Papers
      • 2.4.1.7. Industry Publications
      • 2.4.1.8. Conferences and Seminars
      • 2.4.1.9. Government Portals
      • 2.4.1.10. Media and Press Releases
      • 2.4.1.11. Newsletters
      • 2.4.1.12. Industry Databases
      • 2.4.1.13. Roots Proprietary Databases
      • 2.4.1.14. Paid Databases and Sources
      • 2.4.1.15. Social Media Portals
      • 2.4.1.16. Other Secondary Sources
    • 2.4.2. Primary Research
      • 2.4.2.1. Types of Primary Research
        • 2.4.2.1.1. Qualitative Research
        • 2.4.2.1.2. Quantitative Research
        • 2.4.2.1.3. Hybrid Approach
      • 2.4.2.2. Advantages of Primary Research
      • 2.4.2.3. Techniques for Primary Research
        • 2.4.2.3.1. Interviews
        • 2.4.2.3.2. Surveys
        • 2.4.2.3.3. Focus Groups
        • 2.4.2.3.4. Observational Research
        • 2.4.2.3.5. Social Media Interactions
      • 2.4.2.4. Key Opinion Leaders Considered in Primary Research
        • 2.4.2.4.1. Company Executives (CXOs)
        • 2.4.2.4.2. Board of Directors
        • 2.4.2.4.3. Company Presidents and Vice Presidents
        • 2.4.2.4.4. Research and Development Heads
        • 2.4.2.4.5. Technical Experts
        • 2.4.2.4.6. Subject Matter Experts
        • 2.4.2.4.7. Scientists
        • 2.4.2.4.8. Doctors and Other Healthcare Providers
      • 2.4.2.5. Ethics and Integrity
        • 2.4.2.5.1. Research Ethics
        • 2.4.2.5.2. Data Integrity
    • 2.4.3. Analytical Tools and Databases
  • 2.5. Robust Quality Control

3. MARKET DYNAMICS

  • 3.1. Chapter Overview
  • 3.2. Forecast Methodology
    • 3.2.1. Top-down Approach
    • 3.2.2. Bottom-up Approach
    • 3.2.3. Hybrid Approach
  • 3.3. Market Assessment Framework
    • 3.3.1. Total Addressable Market (TAM)
    • 3.3.2. Serviceable Addressable Market (SAM)
    • 3.3.3. Serviceable Obtainable Market (SOM)
    • 3.3.4. Currently Acquired Market (CAM)
  • 3.4. Forecasting Tools and Techniques
    • 3.4.1. Qualitative Forecasting
    • 3.4.2. Correlation
    • 3.4.3. Regression
    • 3.4.4. Extrapolation
    • 3.4.5. Convergence
    • 3.4.6. Sensitivity Analysis
    • 3.4.7. Scenario Planning
    • 3.4.8. Data Visualization
    • 3.4.9. Time Series Analysis
    • 3.4.10. Forecast Error Analysis
  • 3.5. Key Considerations
    • 3.5.1. Demographics
    • 3.5.2. Government Regulations
    • 3.5.3. Reimbursement Scenarios
    • 3.5.4. Market Access
    • 3.5.5. Supply Chain
    • 3.5.6. Industry Consolidation
    • 3.5.7. Pandemic / Unforeseen Disruptions Impact
  • 3.6. Limitations

4. MACRO-ECONOMIC INDICATORS

  • 4.1. Chapter Overview
  • 4.2. Market Dynamics
    • 4.2.1. Time Period
      • 4.2.1.1. Historical Trends
      • 4.2.1.2. Current and Forecasted Estimates
    • 4.2.2. Currency Coverage
      • 4.2.2.1. Major Currencies Affecting the Market
      • 4.2.2.2. Factors Affecting Currency Fluctuations on the Industry
      • 4.2.2.3. Impact of Currency Fluctuations on the Industry
    • 4.2.3. Foreign Currency Exchange Rate
      • 4.2.3.1. Impact of Foreign Exchange Rate Volatility on the Market
      • 4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
    • 4.2.4. Recession
      • 4.2.4.1. Assessment of Current Economic Conditions and Potential Impact on the Market
      • 4.2.4.2. Historical Analysis of Past Recessions and Lessons Learnt
    • 4.2.5. Inflation
      • 4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
      • 4.2.5.2. Potential Impact of Inflation on the Market Evolution
    • 4.2.6. Interest Rates
      • 4.2.6.1. Interest Rates and Their Impact on the Market
      • 4.2.6.2. Strategies for Managing Interest Rate Risk
    • 4.2.7. Commodity Flow Analysis
      • 4.2.7.1. Type of Commodity
      • 4.2.7.2. Origins and Destinations
      • 4.2.7.3. Values and Weights
      • 4.2.7.4. Modes of Transportation
    • 4.2.8. Global Trade Dynamics
      • 4.2.8.1. Import Scenario
      • 4.2.8.2. Export Scenario
      • 4.2.8.3. Trade Policies
      • 4.2.8.4. Strategies for Mitigating the Risks Associated with Trade Barriers
      • 4.2.8.5. Impact of Trade Barriers on the Market
    • 4.2.9. War Impact Analysis
      • 4.2.9.1. Russian-Ukraine War
      • 4.2.9.2. Israel-Hamas War
    • 4.2.10. COVID Impact / Related Factors
      • 4.2.10.1. Global Economic Impact
      • 4.2.10.2. Industry-specific Impact
      • 4.2.10.3. Government Response and Stimulus Measures
      • 4.2.10.4. Future Outlook and Adaptation Strategies
    • 4.2.11. Other Indicators
      • 4.2.11.1. Fiscal Policy
      • 4.2.11.2. Consumer Spending
      • 4.2.11.3. Gross Domestic Product
      • 4.2.11.4. Employment
      • 4.2.11.5. Taxes
      • 4.2.11.6. Stock Market Performance
      • 4.2.11.7. Cross Border Dynamics
  • 4.3. Conclusion

SECTION II: QUALITATIVE INSIGHTS

5. EXECUTIVE SUMMARY

6. INTRODUCTION

  • 6.1. Chapter Overview
  • 6.2. Introduction to Generative AI
  • 6.3. Evolution of AI
  • 6.4. Applications of Generative AI in Healthcare
    • 6.4.1. Healthcare Research
      • 6.4.1.1. Drug Discovery and Development
    • 6.4.2. Disease Diagnosis and Prognosis
    • 6.4.3. Treatment and Medical Care
    • 6.4.4. Marketing and Administrative Tasks
  • 6.5. Challenges Associated with the Adoption of Generative AI
  • 6.6. Future Perspectives

SECTION III: MARKET OVERVIEW

7. COMPETITIVE LANDSCAPE

  • 7.1. Chapter Overview
  • 7.2. Generative AI Companies in Healthcare: Overall Market Landscape
    • 7.2.1. Analysis by Year of Establishment
    • 7.2.2. Analysis by Company Size
    • 7.2.3. Analysis by Location of Headquarters
    • 7.2.4. Analysis by Company Size and Location of Headquarters (Region)
    • 7.2.5. Analysis by Type of Generative AI Company
    • 7.2.6. Analysis by Type of Offering
    • 7.2.7. Analysis by Application Area
    • 7.2.8. Analysis by End-user

8. COMPANY COMPETITIVENESS ANALYSIS

  • 8.1. Chapter Overview
  • 8.2. Assumptions and Key Parameters
  • 8.3. Methodology
  • 8.4. Generative AI Companies in Healthcare: Company Competitiveness Analysis
    • 8.4.1. Generative AI Companies based in North America
    • 8.4.2. Generative AI Companies based in Europe and Asia-Pacific

SECTION IV: COMPANY PROFILES

9. NORTH AMERICA BASED GENERATIVE AI COMPANIES IN HEALTHCARE

  • 9.1. Chapter Overview
  • 9.2. Detailed Profiles of Generative AI Companies Based in North America
    • 9.2.1. IBM
      • 9.2.1.1. Company Overview
      • 9.2.1.2. Management Team
      • 9.2.1.3. Contact Details
      • 9.2.1.4. Financial Performance
      • 9.2.1.5. Operating Business Segments
      • 9.2.1.6. Generative AI in Healthcare Portfolio
      • 9.2.1.7. Recent Developments and Future Outlook
    • 9.2.2. Microsoft
    • 9.2.3. NVIDIA
    • 9.2.4. OpenAI
  • 9.3. Short Profiles of Generative AI Companies Based in North America
    • 9.3.1. Amazon Web Services
    • 9.3.2. C3 AI
    • 9.3.3. Google
    • 9.3.4. Oracle
    • 9.3.5. Syntegra

10. EUROPE AND ASIA-PACIFIC BASED GENERATIVE AI COMPANIES IN HEALTHCARE

  • 10.1. Chapter Overview
  • 10.2. Detailed Profiles of Generative AI Companies Based in Europe and Asia-Pacific
    • 10.2.1. Huma
      • 10.2.1.1. Company Overview
      • 10.2.1.2. Management Team
      • 10.2.1.3. Contact Details
      • 10.2.1.4. Generative AI in Healthcare Portfolio
      • 10.2.1.5. Recent Developments and Future Outlook
    • 10.2.2. LeewayHertz
  • 10.3. Short Profiles of Generative AI Companies Based in Europe and Asia-Pacific
    • 10.3.1. Exscientia
    • 10.3.2. Iktos
    • 10.3.3. Medical IP
    • 10.3.4. PhamaX

SECTION V: MARKET TRENDS

11. PARTNERSHIPS AND COLLABORATIONS

  • 11.1. Chapter Overview
  • 11.2. Partnership Models
  • 11.3. Generative AI in Healthcare Providers: Partnerships and Collaborations
    • 11.3.1. Analysis by Year of Partnership
    • 11.3.2. Analysis by Type of Partnership
    • 11.3.3. Analysis by Year and Type of Partnership
    • 11.3.4. Analysis by Type of Partner Company
    • 11.3.5. Analysis by Purpose of Partnership
    • 11.3.6. Analysis by Geography
      • 11.3.6.1. Local and International Agreements
      • 11.3.6.2. Intracontinental and Intercontinental Agreements
    • 11.3.7. Most Active Players: Analysis by Number of Partnerships

12. GENERATIVE AI IN HEALTHCARE: USE CASES

  • 12.1. Chapter Overview
  • 12.2. Use Case 1: Collaboration between NVIDIA and Genentech
    • 12.2.1. NVIDIA
    • 12.2.2. Genentech
    • 12.2.3. Business Needs
    • 12.2.4. Objectives Achieved and Solutions Provided
  • 12.3. Use Case 2: Collaboration between Insilico Medicine and Inimmune
    • 12.3.1. Insilico Medicine
    • 12.3.2. Inimmune
    • 12.3.3. Business Needs
    • 12.3.4. Objectives Achieved and Solutions Provided
  • 12.4. Use Case 3: Collaboration between OpenAI and Moderna
    • 12.4.1. OpenAI
    • 12.4.2. Moderna
    • 12.4.3. Business Needs
    • 12.4.4. Objectives Achieved and Solutions Provided
  • 12.5. Use Case 4: Collaboration between Amazon Web Services and Pfizer
    • 12.5.1. Amazon Web Services
    • 12.5.2. Pfizer
    • 12.5.3. Business Needs
    • 12.5.4. Objectives Achieved and Solutions Provided
  • 12.6. Use Case 5: Collaboration between Suki and Ascension Saint Thomas
    • 12.6.1. Suki
    • 12.6.2. Ascension Saint Thomas
    • 12.6.3. Business Needs
    • 12.6.4. Objectives Achieved and Solutions Offered
  • 12.7. Use Case 6: Collaboration between Abridge and Emory Healthcare
    • 12.7.1. Abridge
    • 12.7.2. Emory Healthcare
    • 12.7.3. Business Needs
    • 12.7.4. Objectives Achieved and Solutions Offered
  • 12.8. Use Case 7: Collaboration between Google and China Medical University Hospital
    • 12.8.1. Google
    • 12.8.2. China Medical University Hospital
    • 12.8.3. Business Needs
    • 12.8.4. Objectives Achieved and Solutions Provided

SECTION VI: MARKET OPPORTUNITY ANALYSIS

13. MARKET IMPACT ANALYSIS: DRIVERS, RESTRAINTS, OPPORTUNITIES AND CHALLENGES

  • 13.1. Chapter Overview
  • 13.2. Market Drivers
  • 13.3. Market Restraints
  • 13.4. Market Opportunities
  • 13.5. Market Challenges
  • 13.6. Conclusion

14. GLOBAL GENERATIVE AI IN HEALTHCARE MARKET

  • 14.1. Chapter Overview
  • 14.2. Key Assumptions and Methodology
  • 14.3. Global Generative AI in Healthcare Market, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 14.4. Multivariate Scenario Analysis
    • 14.4.1. Conservative Scenario
    • 14.4.2. Optimistic Scenario
  • 14.5. Key Market Segmentations

15. GENERATIVE AI IN HEALTHCARE MARKET, BY PURPOSE

  • 15.1. Chapter Overview
  • 15.2. Key Assumptions and Methodology
  • 15.3. Generative AI in Healthcare Market: Distribution by Purpose
    • 15.3.1. Generative AI in Healthcare Market for Clinical-based Purpose, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 15.3.2. Generative AI in Healthcare Market for System-based Purpose, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 15.4. Data Triangulation and Validation
    • 15.4.1. Secondary Sources
    • 15.4.2. Primary Sources

16. GENERATIVE AI IN HEALTHCARE MARKET, BY TYPE OF OFFERING

  • 16.1. Chapter Overview
  • 16.2. Key Assumptions and Methodology
  • 16.3. Generative AI in Healthcare Market: Distribution by Type of Offering
    • 16.3.1. Generative AI in Healthcare Market for Technology / Platform, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 16.3.2. Generative AI in Healthcare Market for Services, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.4. Data Triangulation and Validation
    • 16.4.1. Secondary Sources
    • 16.4.2. Primary Sources

17. GENERATIVE AI IN HEALTHCARE MARKET, BY APPLICATION AREA

  • 17.1. Chapter Overview
  • 17.2. Key Assumptions and Methodology
  • 17.3. Generative AI in Healthcare Market: Distribution by Application Area
    • 17.3.1. Generative AI in Healthcare Market for Drug Discovery and Development, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 17.3.2. Generative AI in Healthcare Market for Diagnosis, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 17.3.3. Generative AI in Healthcare Market for Treatment, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 17.3.4. Generative AI in Healthcare Market for Administrative Tasks, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 17.3.5. Generative AI in Healthcare Market for Other Applications, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 17.4. Data Triangulation and Validation
    • 17.4.1. Secondary Sources
    • 17.4.2. Primary Sources

18. GENERATIVE AI IN HEALTHCARE MARKET, BY END-USER

  • 18.1. Chapter Overview
  • 18.2. Key Assumptions and Methodology
  • 18.3. Generative AI in Healthcare Market: Distribution by End-user
    • 18.3.1. Generative AI in Healthcare Market for Pharmaceutical and Life Science Companies, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.3.2. Generative AI in Healthcare Market for Healthcare Providers, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.3.3. Generative AI in Healthcare Market for Other End-users, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.4. Data Triangulation and Validation
    • 18.4.1. Secondary Sources
    • 18.4.2. Primary Sources

19. GENERATIVE AI IN HEALTHCARE MARKET, BY GEOGRAPHICAL REGIONS

  • 19.1. Chapter Overview
  • 19.2. Key Assumptions and Methodology
  • 19.3. Generative AI in Healthcare Market: Distribution by Geographical Regions
    • 19.3.1. Generative AI in Healthcare Market in North America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.1.1. Generative AI in Healthcare Market in the US, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.1.2. Generative AI in Healthcare Market in Canada, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.3.2. Generative AI in Healthcare Market in Europe, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.2.1. Generative AI in Healthcare Market in Germany, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.2.2. Generative AI in Healthcare Market in the UK, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.2.3. Generative AI in Healthcare Market in France, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.2.4. Generative AI in Healthcare Market in Spain, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.2.5. Generative AI in Healthcare Market in Switzerland, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.2.6. Generative AI in Healthcare Market in the Netherlands, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.2.7. Generative AI in Healthcare Market in Rest of Europe, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.3.3. Generative AI in Healthcare Market in Asia-Pacific, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.3.1. Generative AI in Healthcare Market in China, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.3.2. Generative AI in Healthcare Market in Japan, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.3.3. Generative AI in Healthcare Market in South Korea, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.3.4. Generative AI in Healthcare Market in Singapore, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.3.5. Generative AI in Healthcare Market in India, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.3.6. Generative AI in Healthcare Market in Rest of Asia-Pacific, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.3.4. Generative AI in Healthcare Market in Middle East and North Africa, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.4.1. Generative AI in Healthcare Market in Israel, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.4.2. Generative AI in Healthcare Market in UAE, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.4.3. Generative AI in Healthcare Market in Rest of Middle East and North Africa, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.3.5. Generative AI in Healthcare Market in Latin America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.5.1. Generative AI in Healthcare Market in Brazil, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
      • 19.3.5.2. Generative AI in Healthcare Market in Rest of Latin America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.4. Generative AI in Healthcare Market, By Geographical Regions: Market Dynamics Assessment
    • 19.4.1. Penetration-Growth (P-G) Matrix
    • 19.4.2. Market Movement Analysis
  • 19.5. Data Triangulation and Validation
    • 19.5.1. Secondary Sources
    • 19.5.2. Primary Sources

20. GENERATIVE AI IN HEALTHCARE MARKET, BY LEADING PLAYERS

  • 20.1. Chapter Overview
  • 20.2. Key Assumptions and Methodology
  • 20.3. Generative AI in Healthcare Market: Distribution by Leading Generative AI Companies
  • 20.4. Data Triangulation and Validation

21. ADJACENT MARKET ANALYSIS

SECTION VII: STRATEGIC TOOLS

22. PORTER'S FIVE FORCES ANALYSIS

  • 22.1. Chapter Overview
  • 22.2. Significance of Porter's Five Forces Analysis
  • 22.3. Methodology and Assumptions
  • 22.4. Porter's Five Forces
    • 22.4.1. Threats of New Entrants
    • 22.4.2. Bargaining Power of Buyers
    • 22.4.3. Bargaining Power of Generative AI Companies
    • 22.4.4. Threats of Substitute Products
    • 22.4.5. Rivalry Among Existing Competitors
  • 22.5. Concluding Remarks

SECTION VIII: OTHER EXCLUSIVE INSIGHTS

23. INSIGHTS FROM PRIMARY RESEARCH

24. CONCLUDING REMARKS

SECTION IX: APPENDIX

25. TABULATED DATA

26. LIST OF COMPANIES AND ORGANIZATIONS

27. CUSTOMIZATION OPPORTUNITIES

28. ROOTS SUBSCRIPTION SERVICES

29. AUTHOR DETAILS

List of Tables

  • Table 7.1 Generative AI Companies in Healthcare: Information on Year of Establishment, Company Size and Location of Headquarters
  • Table 7.2 Generative AI Companies in Healthcare: Information on Type of Generative AI Company and Type of Offering
  • Table 7.3 Generative AI Companies in Healthcare: Information on Application Area
  • Table 7.4 Generative AI Companies in Healthcare: Information on End-user
  • Table 9.1 Generative AI Companies based in North America: List of Companies Profiled
  • Table 9.2 IBM: Company Overview
  • Table 9.3 IBM: Generative AI in Healthcare Portfolio
  • Table 9.4 IBM: Recent Developments and Future Outlook
  • Table 9.5 Microsoft: Company Overview
  • Table 9.6 Microsoft: Generative AI in Healthcare Portfolio
  • Table 9.7 Microsoft: Recent Developments and Future Outlook
  • Table 9.8 NVIDIA: Company Overview
  • Table 9.9 NVIDIA: Generative AI in Healthcare Portfolio
  • Table 9.10 NVIDIA: Recent Developments and Future Outlook
  • Table 9.11 OpenAI: Company Overview
  • Table 9.12 OpenAI: Generative AI in Healthcare Portfolio
  • Table 9.13 OpenAI: Recent Developments and Future Outlook
  • Table 9.14 Amazon Web Services: Company Overview
  • Table 9.15 Amazon Web Services: Generative AI in Healthcare Portfolio
  • Table 9.16 C3 AI: Company Overview
  • Table 9.17 C3 AI: Generative AI in Healthcare Portfolio
  • Table 9.18 Google: Company Overview
  • Table 9.19 Google: Generative AI in Healthcare Portfolio
  • Table 9.20 Oracle: Company Overview
  • Table 9.21 Oracle: Generative AI in Healthcare Portfolio
  • Table 9.22 Syntegra: Company Overview
  • Table 9.23 Syntegra: Generative AI in Healthcare Portfolio
  • Table 10.1 Generative AI Companies based in Europe and Asia-Pacific: List of Companies Profiled
  • Table 10.2 Huma: Company Overview
  • Table 10.3 Huma: Generative AI in Healthcare Portfolio
  • Table 10.4 Huma: Recent Developments and Future Outlook
  • Table 10.5 LeewayHertz: Company Overview
  • Table 10.6 LeewayHertz: Generative AI in Healthcare Portfolio
  • Table 10.7 LeewayHertz: Recent Developments and Future Outlook
  • Table 10.8 Exscientia: Company Overview
  • Table 10.9 Exscientia: Generative AI in Healthcare Portfolio
  • Table 10.10 Iktos: Company Overview
  • Table 10.11 Iktos: Generative AI in Healthcare Portfolio
  • Table 10.12 Medical IP: Company Overview
  • Table 10.13 Medical IP: Generative AI in Healthcare Portfolio
  • Table 10.14 PhamaX: Company Overview
  • Table 10.15 PhamaX: Generative AI in Healthcare Portfolio
  • Table 11.1 Generative AI Companies in Healthcare: List of Partnerships and Collaborations, Since 2019
  • Table 11.2 Generative AI Companies in Healthcare: Information on Type of Partner Company and Purpose of Partnership
  • Table 11.3 Generative AI Companies in Healthcare: Information on Type of Agreement (Country-wise and Region-wise)
  • Table 23.1 Absci: Company Overview
  • Table 23.2 aiOla: Company Overview
  • Table 23.3 Iktos: Company Overview
  • Table 25.1 Generative AI Companies in Healthcare: Distribution by Year of Establishment
  • Table 25.2 Generative AI Companies in Healthcare: Distribution by Company Size
  • Table 25.3 Generative AI Companies in Healthcare: Distribution by Location of Headquarters
  • Table 25.4 Generative AI Companies in Healthcare: Distribution by Company Size and Location of Headquarters (Region)
  • Table 25.5 Generative AI Companies in Healthcare: Distribution by Type of Generative AI Company
  • Table 25.6 Generative AI Companies in Healthcare: Distribution by Type of Offering
  • Table 25.7 Generative AI Companies in Healthcare: Distribution by Application Area
  • Table 25.8 Generative AI Companies in Healthcare: Distribution by End-user
  • Table 25.9 IBM: Annual Revenues, FY 2021 onwards (USD Million)
  • Table 25.10 Microsoft: Annual Revenues, FY 2021 onwards (USD Million)
  • Table 25.11 NVIDIA: Annual Revenues, FY 2021 onwards (USD Million)
  • Table 25.12 Partnerships and Collaborations: Cumulative Year-wise Trend, Since 2019
  • Table 25.13 Partnerships and Collaborations: Distribution by Type of Partnership
  • Table 25.14 Partnerships and Collaborations: Distribution by Year and Type of Partnership
  • Table 25.15 Partnerships and Collaborations: Distribution by Type of Partner Company
  • Table 25.16 Partnerships and Collaborations: Distribution by Purpose of Partnership
  • Table 25.17 Partnerships and Collaborations: Distribution by Local and International Agreements
  • Table 25.18 Partnerships and Collaborations: Distribution by Intracontinental and Intercontinental Agreements
  • Table 25.19 Most Active Players: Distribution by Number of Partnerships
  • Table 25.20 Global Generative AI in Healthcare Market, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Table 25.21 Global Generative AI in Healthcare Market, Forecasted Estimates (Till 2035): Conservative Scenario (USD Billion)
  • Table 25.22 Global Generative AI in Healthcare Market, Forecasted Estimates (Till 2035): Optimistic Scenario (USD Billion)
  • Table 25.23 Generative AI in Healthcare Market: Distribution by Type of Purpose
  • Table 25.24 Generative AI in Healthcare Market for Clinical-based Purpose, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.25 Generative AI in Healthcare Market for System-based Purpose, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.26 Generative AI in Healthcare Market: Distribution by Type of Offering
  • Table 25.27 Generative AI in Healthcare Market for Technology / Platform, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.28 Generative AI in Healthcare Market for Services, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.29 Generative AI in Healthcare Market: Distribution by Application Area
  • Table 25.30 Generative AI in Healthcare Market for Drug Discovery and Development, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.31 Generative AI in Healthcare Market for Diagnosis, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.32 Generative AI in Healthcare Market for Treatment, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.33 Generative AI in Healthcare Market for Administrative Tasks, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.34 Generative AI in Healthcare Market for Other Applications, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.35 Generative AI in Healthcare Market: Distribution by End-user
  • Table 25.36 Generative AI in Healthcare Market for Pharmaceutical and Life Science Companies, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.37 Generative AI in Healthcare Market for Healthcare Providers, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.38 Generative AI in Healthcare Market for Other End-users, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.39 Generative AI in Healthcare Market: Distribution by Key Geographical Regions
  • Table 25.40 Generative AI in Healthcare Market in North America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.41 Generative AI in Healthcare Market in the US, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.42 Generative AI in Healthcare Market in Canada, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.43 Generative AI in Healthcare Market in Europe, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.44 Generative AI in Healthcare Market in Germany, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.45 Generative AI in Healthcare Market in the UK, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.46 Generative AI in Healthcare Market in France, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.47 Generative AI in Healthcare Market in Spain, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.48 Generative AI in Healthcare Market in Switzerland, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.49 Generative AI in Healthcare Market in the Netherlands, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.50 Generative AI in Healthcare Market in Rest of Europe, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.51 Generative AI in Healthcare Market in Asia-Pacific, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.52 Generative AI in Healthcare Market in China, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.53 Generative AI in Healthcare Market in Japan, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.54 Generative AI in Healthcare Market in South Korea, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.55 Generative AI in Healthcare Market in Singapore, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.56 Generative AI in Healthcare Market in India, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.57 Generative AI in Healthcare Market in Middle East and North Africa, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.58 Generative AI in Healthcare Market in Israel, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.59 Generative AI in Healthcare Market in UAE, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.60 Generative AI in Healthcare Market in Rest of Middle East and North Africa, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.61 Generative AI in Healthcare Market in Latin America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.62 Generative AI in Healthcare Market in Brazil, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.63 Generative AI in Healthcare Market in Rest of Latin America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 25.64 Generative AI in Healthcare Market: Distribution by Leading Generative AI Companies

List of Figures

  • Figure 2.1 Research Methodology: Project Methodology
  • Figure 2.2 Research Methodology: Data Sources for Secondary Research
  • Figure 2.3 Research Methodology: Robust Quality Control
  • Figure 3.1 Market Dynamics: Forecast Methodology
  • Figure 3.2 Market Dynamics: Market Assessment Framework
  • Figure 4.1 Lesson Learnt from Past Recessions
  • Figure 5.1 Executive Summary: Market Landscape
  • Figure 5.2 Executive Summary: Partnerships and Collaborations
  • Figure 5.3 Executive Summary: Market Forecast and Opportunity Analysis
  • Figure 6.1 Workflow of Generative AI
  • Figure 6.2 Evolution of AI
  • Figure 6.3 Applications of Generative AI in Healthcare
  • Figure 6.4 Challenges Associated with the Adoption of Generative AI
  • Figure 7.1 Generative AI Companies in Healthcare: Distribution by Year of Establishment
  • Figure 7.2 Generative AI Companies in Healthcare: Distribution by Company Size
  • Figure 7.3 Generative AI Companies in Healthcare: Distribution by Location of Headquarters
  • Figure 7.4 Generative AI Companies in Healthcare: Distribution by Company Size and Location of Headquarters (Region)
  • Figure 7.5 Generative AI Companies in Healthcare: Distribution by Type of Generative AI Company
  • Figure 7.6 Generative AI Companies in Healthcare: Distribution by Type of Offering
  • Figure 7.7 Generative AI Companies in Healthcare: Distribution by Application Area
  • Figure 7.8 Generative AI Companies in Healthcare: Distribution by End-user
  • Figure 8.1 Company Competitiveness Analysis: Generative AI Companies based in North America
  • Figure 8.2 Company Competitiveness Analysis: Generative AI Companies based in Europe and Asia-Pacific
  • Figure 9.1 IBM: Annual Revenues, FY 2021 onwards (USD Million)
  • Figure 9.2 Microsoft: Annual Revenues, FY 2021 onwards (USD Million)
  • Figure 9.3 NVIDIA: Annual Revenues, FY 2021 onwards (USD Million)
  • Figure 11.1 Partnerships and Collaborations: Cumulative Year-wise Trend, Since 2019
  • Figure 11.2 Partnerships and Collaborations: Distribution by Type of Partnership
  • Figure 11.3 Partnerships and Collaborations: Distribution by Year and Type of Partnership
  • Figure 11.4 Partnerships and Collaborations: Distribution by Type of Partner Company
  • Figure 11.5 Partnerships and Collaborations: Distribution by Purpose of Partnership
  • Figure 11.6 Partnerships and Collaborations: Distribution by Local and International Agreements
  • Figure 11.7 Partnerships and Collaborations: Distribution by Intracontinental and Intercontinental Agreements
  • Figure 11.8 Most Active Players: Distribution by Number of Partnerships
  • Figure 13.1 Global Generative AI in Healthcare Market, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 13.2 Global Generative AI in Healthcare Market, Forecasted Estimates (Till 2035): Conservative Scenario (USD Billion)
  • Figure 13.3 Global Generative AI in Healthcare Market, Forecasted Estimates (Till 2035): Optimistic Scenario (USD Billion)
  • Figure 15.1 Generative AI in Healthcare Market: Distribution by Type of Purpose
  • Figure 15.2 Generative AI in Healthcare Market for Clinical-based Purpose, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 15.3 Generative AI in Healthcare Market for System-based Purpose, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 16.1 Generative AI in Healthcare Market: Distribution by Type of Offering
  • Figure 16.2 Generative AI in Healthcare Market for Technology / Platform, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 16.3 Generative AI in Healthcare Market for Services, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 17.1 Generative AI in Healthcare Market: Distribution by Application Area
  • Figure 17.2 Generative AI in Healthcare Market for Drug Discovery and Development, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 17.3 Generative AI in Healthcare Market for Diagnosis, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 17.4 Generative AI in Healthcare Market for Treatment, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 17.5 Generative AI in Healthcare Market for Administrative Tasks, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 17.6 Generative AI in Healthcare Market for Other Applications, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 18.1 Generative AI in Healthcare Market: Distribution by End-user
  • Figure 18.2 Generative AI in Healthcare Market for Pharmaceutical and Life Science Companies, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 18.3 Generative AI in Healthcare Market for Healthcare Providers, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 18.4 Generative AI in Healthcare Market for Other End-users, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.1 Generative AI in Healthcare Market: Distribution by Key Geographical Regions
  • Figure 19.2 Generative AI in Healthcare Market in North America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.3 Generative AI in Healthcare Market in the US, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.4 Generative AI in Healthcare Market in Canada, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.5 Generative AI in Healthcare Market in Europe, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion) (USD Billion)
  • Figure 19.6 Generative AI in Healthcare Market in Germany, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.7 Generative AI in Healthcare Market in the UK, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.8 Generative AI in Healthcare Market in France, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.9 Generative AI in Healthcare Market in Spain, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.10 Generative AI in Healthcare Market in Switzerland, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.11 Generative AI in Healthcare Market in the Netherlands, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.12 Generative AI in Healthcare Market in Rest of Europe, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.13 Generative AI in Healthcare Market in Asia-Pacific, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.14 Generative AI in Healthcare Market in China, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.15 Generative AI in Healthcare Market in Japan, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.16 Generative AI in Healthcare Market in South Korea, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.17 Generative AI in Healthcare Market in Singapore, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.18 Generative AI in Healthcare Market in India, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.19 Generative AI in Healthcare Market in Rest of Asia-Pacific, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.20 Generative AI in Healthcare Market in Middle East and North Africa, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.21 Generative AI in Healthcare Market in Israel, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.22 Generative AI in Healthcare Market in UAE, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.23 Generative AI in Healthcare Market in Rest of Middle East and North Africa, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.24 Generative AI in Healthcare Market in Latin America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.25 Generative AI in Healthcare Market in Brazil, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.26 Generative AI in Healthcare Market in Rest of Latin America, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035) (USD Billion)
  • Figure 19.27 Penetration-Growth (P-G) Matrix
  • Figure 19.28 Market Movement Analysis
  • Figure 20.1 Generative AI in Healthcare Market: Distribution by Leading Generative AI Companies
  • Figure 22.1 Porter's Five Forces
  • Figure 22.2 Threats of New Entrants: Key Factors
  • Figure 22.3 Bargaining Power of Buyers: Key Factors
  • Figure 22.4 Bargaining Power of Generative AI Companies: Key Factors
  • Figure 22.5 Threats of Substitute Products: Key Factors
  • Figure 22.6 Rivalry Among Existing Competitors: Key Factors
  • Figure 22.7 Porter's Five Forces Analysis: Concluding Remarks
  • Figure 23.1 Concluding Remarks: Market Landscape
  • Figure 23.2 Concluding Remarks: Partnerships and Collaborations
  • Figure 23.3 Concluding Remarks: Market Forecast and Opportunity Analysis