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市場調查報告書

商品編碼

2109151

2026-2035 年醫療保健領域 LLM 和平台模式的市場機會、成長促進因素、產業趨勢和預測。

Healthcare LLM and Foundation Model Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2026 - 2035

出版日期: 2026年07月20日 | 出版商:

Global Market Insights Inc. | 英文 140 Pages | 商品交期: 2-3個工作天內

價格

簡介目錄

全球醫療保健LLM和平台模式市場預計到2025年將達到24億美元，年複合成長率為27.7%，到2035年將達到277億美元。

市場擴張的驅動力在於人工智慧 (AI) 在整個醫療保健生態系統中的快速普及。各機構正投資先進的語言模型和基礎模型，以提高營運效率、臨床準確性和病患療效。對人工智慧驅動的臨床記錄、虛擬護理平台、智慧病人參與解決方案和高級醫療保健分析日益成長的需求，為技術提供者創造了巨大的商機。基礎模型在生命科學研究、精準醫療和基因組學領域的應用不斷擴展，進一步加速了市場發展。此外，多模態人工智慧技術在醫療保健整體的廣泛應用，正在改變醫療服務提供者處理和解讀複雜臨床資訊的方式。隨著醫療機構持續產生大量的結構化和非結構化醫療數據，可擴展人工智慧平台的需求不斷成長，這些平台能夠實現精準洞察、自動化工作流程和數據驅動的決策，從而進一步鞏固了醫療保健語言模型和基礎模型市場的長期發展前景。

市場範圍
開始年份	2025
預測期	2026-2035
起始金額	24億美元
預測金額	277億美元
複合年成長率	27.7%

醫療保健領域的大規模語言模型 (LLM) 和基礎模型市場涵蓋了先進的人工智慧技術，例如大規模語言模型、基於視覺的模型、多模態基礎模型以及基於生物學/基因組學的模型，這些技術專為處理、解釋、分析和生成醫療資訊而開發。這些技術支援廣泛的應用，包括臨床記錄、病人參與、醫學分析、醫學影像、臨床決策支援、醫學編碼、基因組研究和藥物研發。來自醫療記錄、影像系統、基因組資料庫和其他醫療資訊來源的醫療數據持續成長，推動了這些智慧解決方案的普及。醫療機構正擴大採用人工智慧平台來簡化醫療記錄創建流程、最佳化行政工作流程、增強臨床決策、提高編碼準確性並提升營運效率，同時減輕醫生的工作負擔。同時，製藥和生物技術公司也在擴大基礎模型的應用範圍，以提高研究效率、加速治療方案開發、增強生物標記分析並支持臨床開發活動。

預計到2025年，大規模語言模型（LLM）市場佔有率將達到61.2%，這主要得益於醫療機構對人工智慧驅動的文件平台和工作流程自動化技術的需求不斷成長。醫療專用語言模型的廣泛應用將使醫療服務提供者能夠實現臨床文件自動化、匯總患者病歷、簡化編碼流程並降低管理複雜性。這些功能將提高工作效率、提昇文件質量，並使醫療專業人員能夠將更多時間投入到患者照護中，同時最大限度地減少與手動文件流程相關的營運低效問題。

預計到2035年，製藥和生物技術公司細分市場將以28.5%的複合年成長率成長。此細分市場的成長主要得益於生物學和基因組學模型的日益普及，這些模型旨在加速藥物發現、改善標靶發現、加強生物標記研究、最佳化分子設計流程並提高臨床試驗效率。人工智慧在整體研發活動中的廣泛應用，也有助於提高製藥和生技產業的生產力並縮短研發週期。

到2025年，北美醫療保健領域的LLM和平台模式市場佔有率將達到42.5%。先進的醫療基礎設施、電子健康記錄系統的廣泛應用以及對人工智慧技術的持續投資，都將推動該地區的成長。強而有力的數位化醫療轉型措施以及醫院、醫療網路和研究機構對人工智慧平台的日益普及，將繼續推動市場擴張。臨床記錄、病人參與、醫學分析、醫學影像和臨床決策支援等領域智慧解決方案的日益普及，將進一步鞏固該地區在預測期內的主導地位。

產業生態系分析
影響產業的因素
- 成長促進因素
  - 臨床文件自動化的需求日益成長
  - 人工智慧在藥物研發和基因組研究領域的應用正在加速。
  - 以價值為導向的醫療保健模式的擴展將透過人工智慧促進患者參與。
  - 醫療數據量的不斷成長使得建立更大規模、更精確的基礎模型成為可能。
- 產業潛在風險與挑戰
  - 資料隱私和 HIPAA 合規性挑戰
  - 引入大規模模型會帶來高昂的運算和運行成本。
- 市場機遇
  - 多模態人工智慧應用於診斷、病理學和基因組學領域。
  - 低成本的雲端技術應用使進入醫療服務供應不足的市場成為可能。
成長潛力分析
監理情勢
技術展望
- 最新科技趨勢
- 新興技術
價格趨勢分析
未來市場趨勢
波特的分析
PESTLE分析
人工智慧和生成式人工智慧對市場的影響
差距分析

第4章競爭情勢

介紹
企業矩陣分析
企業市佔率分析
- 世界
- 北美洲
- 歐洲
- 亞太地區
競爭定位矩陣
主要市場公司的競爭分析
主要進展
- 併購
- 夥伴關係和聯盟
- 新產品發布
- 業務拓展計劃

第5章市場估價與預測：依車型分類，2022-2035年

大規模語言模型（LLM）
- 臨床實踐和文檔方面的LLM
- 病人參與的LLM
- 生物醫學研究法學碩士
基於視覺的模型
多模態平台模型
生物學和基因組模型

第6章市場估算與預測：依部署模式分類，2022-2035年

基於雲端的
現場

第7章市場估計與預測：依應用領域分類，2022-2035年

臨床文件
醫學影像診斷
藥物發現與開發
患者參與
其他用途

第8章市場估算與預測：依最終用途分類，2022-2035年

醫院
製藥和生物技術公司
付款人
研究機構
其他最終用戶

第9章市場估計與預測：依地區分類，2022-2035年

北美洲
- 美國
- 加拿大
歐洲
- 德國
- 英國
- 法國
- 西班牙
- 義大利
- 荷蘭
亞太地區
- 中國
- 日本
- 印度
- 澳洲
- 韓國
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
中東和非洲
- 南非
- 沙烏地阿拉伯
- UAE

第10章：公司簡介

Abridge
Aidoc
Amazon Web Services
Ambience Healthcare
Anthropic
BenevolentAI
Elsevier
Google
Hippocratic AI
Hyro
Insilico Medicine
Isomorphic Labs
Microsoft
Nabla
NVIDIA
OpenAI
Orbita
Paige AI
Recursion Pharmaceuticals
Suki AI
Tempus AI
Viz.ai

簡介目錄

Product Code: 16367

The Global Healthcare LLM and Foundation Model Market was valued at USD 2.4 billion in 2025 and is estimated to grow at a CAGR of 27.7% to reach USD 27.7 billion by 2035.

Healthcare LLM and Foundation Model Market - IMG1

Market expansion is being fueled by the rapid adoption of artificial intelligence across the healthcare ecosystem, where organizations are investing in advanced language and foundation models to improve operational efficiency, clinical accuracy, and patient outcomes. Rising demand for AI-enabled clinical documentation, virtual care platforms, intelligent patient engagement solutions, and advanced healthcare analytics is creating substantial opportunities for technology providers. The growing use of foundation models in life sciences research, precision medicine, and genomics is further accelerating market development. In addition, increasing implementation of multimodal AI technologies across healthcare operations is transforming the way providers process and interpret complex clinical information. As healthcare organizations continue generating massive volumes of structured and unstructured medical data, the need for scalable AI-powered platforms capable of delivering accurate insights, workflow automation, and data-driven decision-making continues to strengthen the long-term outlook for the healthcare LLM and foundation model market.

Market Scope
Start Year	2025
Forecast Year	2026-2035
Start Value	$2.4 Billion
Forecast Value	$27.7 Billion
CAGR	27.7%

The healthcare LLM and foundation model market comprises advanced artificial intelligence technologies, including large language models, vision foundation models, multimodal foundation models, and biological and genomic foundation models developed to process, interpret, analyze, and generate healthcare-related information. These technologies support a broad range of applications, including clinical documentation, patient engagement, healthcare analytics, medical imaging, clinical decision support, medical coding, genomics research, and drug discovery. Continuous growth in healthcare data generated from clinical records, imaging systems, genomic databases, and other healthcare sources is driving wider adoption of these intelligent solutions. Healthcare organizations are increasingly integrating AI-driven platforms to streamline documentation, optimize administrative workflows, strengthen clinical decision-making, improve coding accuracy, and enhance operational performance while reducing physician workload. At the same time, pharmaceutical and biotechnology organizations are expanding the use of foundation models to improve research efficiency, accelerate therapeutic development, enhance biomarker analysis, and support clinical development activities.

The large language models (LLMs) segment accounted for a 61.2% share in 2025, supported by increasing demand for AI-powered documentation platforms and workflow automation technologies across healthcare organizations. Growing implementation of healthcare-focused language models enables providers to automate clinical documentation, summarize patient records, streamline coding processes, and reduce administrative complexity. These capabilities improve productivity, enhance documentation quality, and allow healthcare professionals to dedicate more time to patient care while minimizing operational inefficiencies associated with manual documentation processes.

The pharmaceutical and biotechnology companies segment is projected to grow at a CAGR of 28.5% throughout 2035. Market growth within this segment is supported by increasing adoption of biological and genomic foundation models to accelerate drug development, improve target discovery, strengthen biomarker research, optimize molecular design processes, and enhance clinical trial efficiency. The expanding application of artificial intelligence throughout research and development activities continues to improve productivity while reducing development timelines across the pharmaceutical and biotechnology industries.

North America Healthcare LLM and Foundation Model Market held a 42.5% share in 2025. Regional growth is supported by advanced healthcare infrastructure, widespread adoption of electronic health record systems, and continued investments in artificial intelligence technologies. Strong digital healthcare transformation initiatives and increasing implementation of AI-powered platforms across hospitals, healthcare networks, and research organizations continue to support market expansion. Growing adoption of intelligent solutions for clinical documentation, patient engagement, healthcare analytics, medical imaging, and clinical decision support is further strengthening the region's leadership position throughout the forecast period.

Key Players in the Global Healthcare LLM and Foundation Model Market include Microsoft, Tempus AI, Orbita, BenevolentAI, OpenAI, Amazon Web Services, Hyro, Abridge, NVIDIA, Google, Paige AI, Anthropic, Suki AI, Elsevier, Isomorphic Labs, Nabla, Aidoc, Viz.ai, Ambience Healthcare, Hippocratic AI, Insilico Medicine, Recursion Pharmaceuticals. Companies operating in the healthcare LLM and foundation model market are strengthening their competitive position through continuous investments in artificial intelligence innovation, healthcare-specific model development, and strategic collaborations with healthcare providers, research organizations, and life sciences companies. Market participants are expanding their product portfolios by introducing specialized AI solutions that improve clinical workflows, automate documentation, and enhance decision support capabilities. Organizations are also investing heavily in cloud-based infrastructure, data security, regulatory compliance, and scalable deployment models to meet the evolving needs of healthcare institutions. In addition, companies are prioritizing research and development to improve model accuracy, multimodal capabilities, and interoperability with existing healthcare systems. Geographic expansion, strategic acquisitions, long-term technology partnerships, and continuous platform enhancements remain key initiatives for strengthening market presence and maintaining a competitive advantage.

Chapter 1 Research Methodology

1.1 Research approach
1.2 Quality commitments
- 1.2.1 GMI AI policy & data integrity commitment
  - 1.2.1.1 Source consistency protocol
1.3 Research trail & confidence scoring
- 1.3.1 Research trail components
- 1.3.2 Scoring components
1.4 Data collection
- 1.4.1 Partial list of primary sources
1.5 Data mining sources
- 1.5.1 Paid sources
  - 1.5.1.1 Sources, by region
1.6 Base estimates and calculations
- 1.6.1 Base year calculation for any one approach
1.7 Forecast model
- 1.7.1 Quantified market impact analysis
  - 1.7.1.1 Mathematical impact of growth parameters on forecast
1.8 Research transparency addendum
- 1.8.1 Source attribution framework
- 1.8.2 Quality assurance metrics
- 1.8.3 Our commitment to trust

Chapter 2 Executive Summary

2.1 Industry 360° synopsis
2.2 Key market trends
- 2.2.1 Regional trends
- 2.2.2 Model type trends
- 2.2.3 Deployment mode trends
- 2.2.4 Application trends
- 2.2.5 End use trends
2.3 CXO perspectives: Strategic imperatives

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
3.2 Industry impact forces
- 3.2.1 Growth drivers
  - 3.2.1.1 Rising demand for clinical documentation automation
  - 3.2.1.2 Accelerating adoption of AI in drug discovery & genomics research
  - 3.2.1.3 Expansion of value-based care models driving patient engagement AI
  - 3.2.1.4 Growing healthcare data volumes enabling larger and more accurate foundation models
- 3.2.2 Industry pitfalls and challenges
  - 3.2.2.1 Data privacy, HIPAA compliance challenges
  - 3.2.2.2 High compute and operational costs for large-scale model deployment
- 3.2.3 Market opportunities
  - 3.2.3.1 Multimodal AI integration across diagnostics, pathology & genomics
  - 3.2.3.2 Expansion into underserved healthcare markets via low-cost cloud deployment
3.3 Growth potential analysis
3.4 Regulatory landscape (Driven by primary research)
- 3.4.1 North America
- 3.4.2 Europe
- 3.4.3 Asia Pacific
- 3.4.4 Latin America
- 3.4.5 MEA
3.5 Technology landscape
- 3.5.1 Current technological trends
- 3.5.2 Emerging technologies
3.6 Pricing trend analysis (Driven by primary research)
3.7 Future market trends
3.8 Porter's analysis
3.9 PESTEL analysis
3.10 Impact of AI and Generative AI on the market (Driven by primary research)
3.11 Gap analysis

Chapter 4 Competitive Landscape, 2025

4.1 Introduction
4.2 Company matrix analysis
4.3 Company market share analysis (Driven by primary research)
- 4.3.1 Global
- 4.3.2 North America
- 4.3.3 Europe
- 4.3.4 Asia Pacific
4.4 Competitive positioning matrix
4.5 Competitive analysis of major market players
4.6 Key developments
- 4.6.1 Mergers & acquisitions
- 4.6.2 Partnerships & collaborations
- 4.6.3 New product launches
- 4.6.4 Expansion plans

Chapter 5 Market Estimates and Forecast, By Model Type, 2022 - 2035 ($ Mn)

5.1 Key trends
5.2 Large language models (LLMs)
- 5.2.1 Clinical and documentation LLMs
- 5.2.2 Patient engagement LLMs
- 5.2.3 Biomedical research LLMs
5.3 Vision foundation models
5.4 Multimodal foundation models
5.5 Biological and genomic foundation models

Chapter 6 Market Estimates and Forecast, By Deployment Mode, 2022 - 2035 ($ Mn)

6.1 Key trends
6.2 Cloud-based
6.3 On-premise

Chapter 7 Market Estimates and Forecast, By Application, 2022 - 2035 ($ Mn)

7.1 Key trends
7.2 Clinical documentation
7.3 Medical imaging
7.4 Drug discovery and development
7.5 Patient engagement
7.6 Other applications

Chapter 8 Market Estimates and Forecast, By End Use, 2022 - 2035 ($ Mn)

8.1 Key trends
8.2 Hospitals
8.3 Pharmaceutical and biotechnology companies
8.4 Payers
8.5 Research institutions
8.6 Other end users

Chapter 9 Market Estimates and Forecast, By Region, 2022 - 2035 ($ Mn)

9.1 Key trends
9.2 North America
- 9.2.1 U.S.
- 9.2.2 Canada
9.3 Europe
- 9.3.1 Germany
- 9.3.2 UK
- 9.3.3 France
- 9.3.4 Spain
- 9.3.5 Italy
- 9.3.6 Netherlands
9.4 Asia Pacific
- 9.4.1 China
- 9.4.2 Japan
- 9.4.3 India
- 9.4.4 Australia
- 9.4.5 South Korea
9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Argentina
9.6 Middle East and Africa
- 9.6.1 South Africa
- 9.6.2 Saudi Arabia
- 9.6.3 UAE