美國醫療保健 AI 市場：服務細分和最終用戶的分析和預測（2024-2034 年）

美國醫療保健 AI 市場規模預計將從 2023 年的 52.543 億美元成長到 2034 年的 2,2969.94 億美元，預測期內複合年成長率高達 40.41%。

這一令人印象深刻的成長是由快速的技術進步所推動的，這些技術從根本上重塑了醫療保健服務。機器學習和深度學習演算法的突破性進展正在推動高精度診斷工具和個人化治療方案的發展，從而改善患者的治療效果和業務效率。穿戴式裝置和遠端醫療等數位健康解決方案的整合將進一步擴展人工智慧的功能，實現即時監控和遠端病患管理。來自私人和公共部門的大量投資正在加速研究和開發，促進創新和應用的持續循環。此外，支援性的監管環境和行業相關利益者之間的策略夥伴關係為在傳統醫療保健框架內無縫採用人工智慧解決方案鋪平了道路，促進了知識交流和技術整合。這些因素將支持未來十年美國醫療保健人工智慧市場的快速成長並創造強大的生態系統。

在產品供應方面，軟體和服務業處於領先地位：

根據產品細分，軟體和服務細分市場將在 2023 年以 72% 的佔有率引領市場。我們的軟體和服務提供全面的解決方案，包括預測分析和輔助診斷到電子健康記錄整合和自然語言處理，幫助醫療保健提供者提高臨床決策和業務效率。這些工具可實現即時資料處理和個人化治療計劃，最終有助於改善患者的治療效果並顯著節省成本。就像先進的作業系統可以無縫整合不同的應用程式以最佳化效能一樣，這些軟體主導的解決方案是醫療保健數位轉型的支柱，簡化了工作流程並促進更快、更準確的診斷。隨著對數位健康創新的持續投入，軟體和服務的重要性預計將繼續成長，並在塑造更有效率、以患者為中心的醫療保健環境中發揮關鍵作用。

按最終用戶分類，其他醫療保健提供者細分市場占主導地位：

根據最終用戶，其他醫療保健提供者部門在 2023 年佔據 46% 的市場佔有率，佔據市場主導地位。其他醫療保健提供者包括專科診斷中心、門診診所、門診護理中心和獨立實驗室。這些營業單位擴大採用人工智慧主導的測試解決方案來提高診斷準確性，減少週轉時間，並客製化治療通訊協定以獲得更好的患者結果。透過利用先進的演算法和即時資料分析，我們可以識別傳統測試方法可能忽略的模式和異常。就像互聯醫療保健系統中的專家網路一樣，這些提供者在擴大尖端診斷技術的使用範圍、推動醫療保健的數位轉型以及最終有助於提供更高效、個性化的醫療服務方面發揮關鍵作用。

市場區隔

細分一：按產品

• 硬體
• 軟體與服務

細分 2：按最終用戶

• 醫療保健提供者
• 醫療支付者
• 病人
• 其他醫療保健提供者

本報告研究了美國醫療保健AI市場，並總結了主要趨勢、影響市場的因素分析、法律制度、技術發展和專利趨勢、案例研究、市場規模趨勢和預測、各個細分市場的詳細分析、競爭格局以及主要企業的概況。

目錄

執行摘要

範圍和定義

第1章市場：產業展望

• 市場概況
  • 醫療人工智慧簡介
  • 醫療保健人工智慧的用案例
  • 人工智慧所使用的技術
• 市場趨勢和採用率
  • 擴大數位技術的採用
  • 擴大資金籌措力度
  • 醫療人工智慧的新應用
• 人工智慧的採用和市場準備
• 進入障礙和機會
• 案例研究和影響
• 監管狀態
• 市場動態概覽
  • 影響分析
  • 市場促進因素
  • 市場挑戰
  • 市場機會

第 2 章：美國醫療保健 AI 市場（按服務細分）

• 硬體
• 軟體與服務

第 3美國。

• 醫療保健提供者
• 醫療支付者
• 病人
• 其他醫療保健提供者

第 4 章市場：競爭基準化分析與公司簡介

• 關鍵策略和發展
• 投資格局（資金籌措和併購活動）
• 主要 AI 產品和Start-Ups
  • Viz.ai
  • Abridge
  • Insilico Medicine
  • Tempus
• 公司簡介
  • International Business Machines Corporation
  • Google LLC
  • Microsoft Corporation
  • Amazon.com, Inc.
  • NVIDIA Corporation
  • GE HealthCare
  • Koninklijke Philips NV
  • Tempus Labs, Inc.
  • PathAI

第5章調查方法

Introduction of U.S. AI in Healthcare Market

The U.S. AI in healthcare market, initially valued at $5,254.3 million in 2023, is set for substantial growth, projected to surge to $229,699.4 million by 2034, marking a remarkable compound annual growth rate (CAGR) of 40.41% over the period from 2024 to 2034. This impressive trajectory is fuelled by rapid technological advancements that are fundamentally reshaping healthcare delivery. Breakthroughs in machine learning and deep learning algorithms drive the development of highly accurate diagnostic tools and personalized treatment plans, improving patient outcomes and operational efficiencies. The integration of digital health solutions, such as wearable devices and telemedicine, further expands the capabilities of AI, enabling real-time monitoring and remote patient management. Significant investments from both private and public sectors are accelerating research and development, fostering a continuous cycle of innovation and application. Additionally, a supportive regulatory environment is paving the way for seamless adoption of AI solutions within traditional healthcare frameworks, while strategic partnerships among industry stakeholders are facilitating knowledge exchange and technological integration. Together, these factors create a robust ecosystem that not only supports but actively propels the rapid growth of the U.S. AI in healthcare market over the coming decade.

Market Introduction

The AI in healthcare market in the U.S. has been experiencing significant growth, driven by rapid technological innovation, evolving regulatory support, and a surge in strategic investments. Advanced AI applications, including predictive analytics and sophisticated diagnostic tools, are transforming traditional healthcare practices by enabling more accurate and timely clinical decision-making. This shift is further bolstered by the integration of digital health solutions, such as wearable devices and telemedicine, which facilitate continuous patient monitoring and remote care. Additionally, healthcare providers are increasingly embracing data-driven approaches to enhance personalized treatment protocols and improve overall patient outcomes. As these technological advancements align with a broader move towards preventive care and operational efficiency, the U.S. AI in healthcare market is witnessing a paradigm shift reshaping healthcare delivery's future.

Industrial Impact

The U.S. AI in healthcare market is set for steady growth, driven by rapid technological advancements, supportive regulatory frameworks, and increased investments in digital health innovation. Emerging AI algorithms and machine learning platforms are enhancing diagnostic accuracy and enabling personalized treatment plans, while streamlined government initiatives and evolving FDA guidelines are creating an environment conducive to integrating AI into clinical practices.

The industrial impact of AI in healthcare is profound, fundamentally reshaping clinical processes and operational efficiencies across the sector. AI-driven solutions have been shown to reduce diagnostic errors by up to 30%, leading to more accurate treatments and significant cost savings, bolstering the $500 million in venture capital funding secured by U.S.-based healthcare AI startups in 2023. This influx of investment is accelerating innovation, paving the way for advanced diagnostic tools and predictive analytics that are streamlining workflows in hospitals and clinics alike. Moreover, governmental initiatives, including those by the U.S. Department of Health and Human Services, project up to $150 billion in annual savings by 2026 through optimized treatment protocols and reduced misdiagnoses. These factors collectively are not only enhancing patient outcomes but are also transforming healthcare institutions into agile, data-driven entities, much like a well-orchestrated industrial upgrade that replaces outdated systems with next-generation technologies, thereby setting new benchmarks for efficiency and quality in healthcare delivery.

Market Segmentation:

Segmentation 1: by Offering

• Hardware
• Software and Services

Software and Services Offering Segment to Dominate the U.S. AI in Healthcare Market (by Offering)

Based on offering, the U.S. AI in healthcare market was led by the software and services offering segment, which held a 72% share in 2023. Software and services offer a comprehensive suite of solutions, ranging from predictive analytics and diagnostic support to electronic health record integration and natural language processing, that empower healthcare providers to enhance clinical decision-making and operational efficiency. These tools enable real-time data processing and personalized treatment planning, ultimately contributing to improved patient outcomes and significant cost savings. Much like an advanced operating system that seamlessly integrates various applications to optimize performance, these software-driven solutions serve as the backbone of digital transformation in healthcare, streamlining workflows and facilitating faster, more accurate diagnoses. With ongoing investments in digital health innovation, the prominence of software and services is expected to continue expanding, solidifying its pivotal role in shaping a more efficient and patient-centric healthcare landscape.

Segmentation 2: by End User

• Healthcare Providers
• Healthcare Payers
• Patients
• Other Healthcare Providers

Other Healthcare Providers Segment to Dominate the U.S. AI in Healthcare Market (by End User)

Based on the end user, the U.S. AI in healthcare market was led by the other healthcare providers segment, which held a 46% share in 2023. Other healthcare providers are a diverse group that includes specialized diagnostic centers, outpatient clinics, ambulatory care centers, and independent laboratories. These entities are increasingly adopting AI-driven testing solutions to enhance diagnostic accuracy, reduce turnaround times, and tailor treatment protocols for better patient outcomes. By leveraging advanced algorithms and real-time data analytics, they are able to identify patterns and anomalies that might otherwise be overlooked in traditional testing methods. Much like a network of interconnected specialists in a well-coordinated healthcare system, these providers play a crucial role in expanding access to cutting-edge diagnostic technologies, driving the digital transformation of healthcare, and ultimately contributing to more efficient and personalized care delivery.

Recent Developments in the U.S. AI in Healthcare Market

• In October 2023, Medtronic Plc partnered with Nvidia to build an AI platform for medical devices.
• In July 2022, Amazon.com, Inc. acquired One Medical for $3.9 billion, expanding AI-enabled primary care.

Demand - Drivers, Challenges, and Opportunities

Market Drivers:

Growing Need for Early Detection and Diagnosis: The growing need for early detection and diagnosis has become increasingly critical as the complexity of healthcare challenges continues to rise. Timely identification of diseases allows for prompt and targeted intervention, which can significantly enhance treatment effectiveness. Innovative diagnostic technologies, particularly AI-powered, enable clinicians to detect subtle changes and early warning signs that might otherwise go unnoticed. Early diagnosis paves the way for personalized care plans and reduces the risk of severe complications. By shifting the focus toward prevention rather than reaction, healthcare systems are better equipped to manage patient outcomes proactively. This proactive approach alleviates long-term burdens on healthcare resources and minimizes overall treatment costs. Ultimately, the emphasis on early detection is driving a transformative shift toward precision medicine and a more sustainable future for patient care.

Market Challenges:

Concerns Regarding Data Privacy: Data privacy concerns in healthcare have become increasingly significant as AI systems process vast amounts of sensitive patient information. The aggregation of data from diverse sources introduces vulnerabilities that can lead to unauthorized access and data breaches, putting personal health records at risk. Regulatory frameworks, although robust, often struggle to keep pace with rapid technological advancements and the complexities of cross-border data flows. This situation underscores the challenge of balancing the benefits of AI-driven healthcare innovations with the imperative to protect patient confidentiality. Healthcare organizations are, therefore, investing heavily in cybersecurity measures, such as advanced encryption and data anonymization, to mitigate these risks. At the same time, ongoing updates to privacy regulations and best practices are essential to address evolving cyber threats. Ultimately, maintaining stringent data protection protocols is critical to preserving patient trust and ensuring the ethical use of AI in healthcare.

Market Opportunities:

Pain Management and Personalized Care: AI-driven innovations are revolutionizing pain management by offering highly personalized care tailored to each patient's unique needs. Continuous monitoring through wearable devices and sensors captures real-time data on pain levels, enabling clinicians to adjust treatments promptly and effectively. Advanced data analytics identify individual pain triggers and patterns, paving the way for targeted and efficient interventions. Enhanced diagnostic imaging further refines these approaches by accurately pinpointing the sources of pain, which supports the development of more precise treatment strategies. Integration with telemedicine platforms also plays a crucial role, allowing remote monitoring and timely consultations that ensure care remains responsive and accessible. By combining historical patient data with live insights, clinicians can create dynamic pain management plans that evolve with each patient's condition. Ultimately, this personalized approach improves pain control and enhances overall quality of life, empowering patients through tailored, proactive care.

How can this report add value to an organization?

Product/Innovation Strategy: The U.S. AI in healthcare market has been extensively segmented based on various categories, such as offerings and end users. This can help readers understand which segments account for the largest share and which are well-positioned to grow in the coming years.

Growth/Marketing Strategy: Mergers, acquisitions, and product launches accounted for the maximum number of key developments, i.e., nearly 41.67% of the total developments in the U.S. AI in healthcare market were between January 2019 and December 2023.

Competitive Strategy: The U.S. AI in healthcare market has numerous established players with product portfolios. Key players in the U.S. AI in healthcare market analyzed and profiled in the study involve established players offering products for U.S. AI in healthcare.

Methodology

Key Considerations and Assumptions in U.S. AI in Healthcare Market Engineering and Validation

• The base year considered for the calculation of the U.S. AI in healthcare market size is 2023. A historical year analysis has been done for the period FY2021-FY2022. The U.S. AI in healthcare market size has been estimated for FY2023 and projected for the period FY2024-FY2034.
• The scope of this report has been carefully derived based on interactions with experts in different companies. This report provides a market study of upstream and downstream technologies of the U.S. AI in healthcare market.
• The U.S. AI in healthcare market contribution of U.S. AI in healthcare is anticipated to be launched and calculated based on a historical analysis of the solutions.
• The company's revenue has been referenced from their annual reports for FY2022 and FY2023. For private companies, revenues have been estimated based on factors such as inputs obtained from primary research, funding history, market collaborations, and operational history.
• The U.S. AI in healthcare market has been mapped based on the available U.S. AI in healthcare data. This report has considered and profiled all the key companies with significant offerings in this field.

Primary Research:

The primary sources involve industry experts in U.S. AI in healthcare, including the market players offering products and services. Resources such as CEOs, vice presidents, marketing directors, and technology and innovation directors have been interviewed to obtain and verify both qualitative and quantitative aspects of this research study.

The key data points taken from the primary sources include:

• Validation and triangulation of all the numbers and graphs
• Validation of the report's segmentation and key qualitative findings
• Understanding the competitive landscape and business model
• Current and proposed production values of a product by market players
• Validation of the numbers of the different segments of the U.S. AI in healthcare market in focus
• Percentage split of individual markets for regional analysis

Secondary Research

Open Sources

• Certified publications, articles from recognized authors, white papers, directories, and major databases, among others
• Annual reports, SEC filings, and investor presentations of the leading market players
• Company websites and detailed study of their product portfolio
• Gold standard magazines, journals, white papers, press releases, and news articles
• Paid databases

The key data points taken from the secondary sources include:

• Segmentations and percentage shares
• Data for market value
• Key industry trends of the top players of the U.S. AI in healthcare market
• Qualitative insights into various aspects of the U.S. AI in healthcare market, key trends, and emerging areas of innovation
• Quantitative data for mathematical and statistical calculations

Key Market Players and Competition Synopsis

Profiled companies have been selected based on inputs gathered from primary experts, who have analysed company coverage, product portfolio, and market penetration.

Some prominent names established in this market are:

• International Business Machines Corporation
• Google LLC
• Microsoft Corporation
• Amazon.com, Inc.
• NVIDIA Corporation
• GE HealthCare

Table of Contents

Executive Summary

Scope and Definition

1 Market: Industry Outlook

• 1.1 Market Overview
  • 1.1.1 AI Adoption in Healthcare
  • 1.1.2 AI Use Cases in Healthcare
    • 1.1.2.1 Diagnostics and Imaging
    • 1.1.2.2 Drug Discovery and Development
    • 1.1.2.3 Personalized Medicine and Treatment Plans
    • 1.1.2.4 AI in Patient Management and Virtual Healthcare
    • 1.1.2.5 Remote Patient Monitoring (RPM)
    • 1.1.2.6 Hospital Operations and Administrative Automation
    • 1.1.2.7 AI in Surgery and Robotics
    • 1.1.2.8 AI for Disease Prediction and Early Detection
  • 1.1.3 Technology Used in AI
    • 1.1.3.1 Machine Learning
    • 1.1.3.2 Natural Language Processing (NLP)
    • 1.1.3.3 Generative AI
    • 1.1.3.4 Computer Vision
    • 1.1.3.5 Image Analysis
• 1.2 Market Trends and Adoption Rates
  • 1.2.1 Increasing Adoption of Digital Technology
  • 1.2.2 Increasing Funding Initiatives
  • 1.2.3 Emerging Applications of AI in Healthcare
• 1.3 AI Adoption vs Market Readiness
• 1.4 Entry Barriers and Opportunities
  • 1.4.1 Barriers
    • 1.4.1.1 Regulatory Uncertainty
    • 1.4.1.2 Integration Complexity
    • 1.4.1.3 Workforce Transition
    • 1.4.1.4 Data Strategy
    • 1.4.1.5 ROI Realization
  • 1.4.2 Opportunities
    • 1.4.2.1 Strategic Differentiation
    • 1.4.2.2 New Services and Revenue Streams
    • 1.4.2.3 Addressing Workforce Shortages
    • 1.4.2.4 Collaboration and Ecosystem Building
• 1.5 Case Studies and Impact
  • 1.5.1 Stroke Care (Viz.ai)
  • 1.5.2 Sepsis Early Detection-Mixed Results
  • 1.5.3 Diagnostic Accuracy
  • 1.5.4 Patient Satisfaction-AI Patient Communication
  • 1.5.5 Telehealth Triage-Kaiser's Chatbot
• 1.6 Regulatory Landscape
  • 1.6.1 Regulatory and Policy Landscape in the U.S.
  • 1.6.2 EU vs. U.S. Differences
• 1.7 Market Dynamics Overview
  • 1.7.1 Impact Analysis
  • 1.7.2 Market Drivers
    • 1.7.2.1 Growing Need for Early Detection and Diagnosis
    • 1.7.2.2 The Rapid Proliferation of AI in the Healthcare Sector
    • 1.7.2.3 Exponential Growth in Data Volume and Complexity Due to Surging Adoption of Digital Technologies
    • 1.7.2.4 Operational Efficiency and Cost Reduction
  • 1.7.3 Market Challenges
    • 1.7.3.1 Concerns Regarding Data Privacy
  • 1.7.4 Market Opportunities
    • 1.7.4.1 Pain Management and Personalized Care

2 U.S. AI in Healthcare Market (by Offering), $Billion, 2023-2034

• 2.1 Hardware
• 2.2 Software and Services

3 U.S. AI in Healthcare Market (by End User), $Billion, 2023-2034

• 3.1 Healthcare Providers
• 3.2 Healthcare Payers
• 3.3 Patients
• 3.4 Other Healthcare Providers

4 Markets - Competitive Benchmarking & Company Profiles

• 4.1 Key Strategies and Development
  • 4.1.1 Partnerships, Alliances, and Business Expansions
  • 4.1.2 Funding Activities
  • 4.1.3 Merger and Acquisition
  • 4.1.4 New Offerings and Regulatory Approval
• 4.2 Investment Landscape (Funding and M&A Activity)
• 4.3 Major AI Products and Startups (2023-2025)
  • 4.3.1 Viz.ai
  • 4.3.2 Abridge
  • 4.3.3 Insilico Medicine
  • 4.3.4 Tempus
• 4.4 Company Profiles
  • 4.4.1 International Business Machines Corporation
    • 4.4.1.1 Overview
    • 4.4.1.2 Top Products/Services
    • 4.4.1.3 Top Competitors
    • 4.4.1.4 Target Customers
    • 4.4.1.5 Analyst View
  • 4.4.2 Google LLC
    • 4.4.2.1 Overview
    • 4.4.2.2 Top Products/Services
    • 4.4.2.3 Top Competitors
    • 4.4.2.4 Target Customers
    • 4.4.2.5 Analyst View
  • 4.4.3 Microsoft Corporation
    • 4.4.3.1 Overview
    • 4.4.3.2 Top Products/ Services
    • 4.4.3.3 Top Competitors
    • 4.4.3.4 Target Customers
    • 4.4.3.5 Analyst View
  • 4.4.4 Amazon.com, Inc.
    • 4.4.4.1 Overview
    • 4.4.4.2 Top Products/ Services
    • 4.4.4.3 Top Competitors
    • 4.4.4.4 Target Customers
    • 4.4.4.5 Analyst View
  • 4.4.5 NVIDIA Corporation
    • 4.4.5.1 Overview
    • 4.4.5.2 Top Products/ Services
    • 4.4.5.3 Top Competitors
    • 4.4.5.4 Target Customers
    • 4.4.5.5 Analyst View
  • 4.4.6 GE HealthCare
    • 4.4.6.1 Overview
    • 4.4.6.2 Top Products/ Services
    • 4.4.6.3 Top Competitors
    • 4.4.6.4 Target Customers
    • 4.4.6.5 Analyst View
  • 4.4.7 Koninklijke Philips N.V.
    • 4.4.7.1 Overview
    • 4.4.7.2 Top Products/ Services
    • 4.4.7.3 Top Competitors
    • 4.4.7.4 Target Customers
    • 4.4.7.5 Analyst View
  • 4.4.8 Tempus Labs, Inc.
    • 4.4.8.1 Overview
    • 4.4.8.2 Top Products/ Services
    • 4.4.8.3 Top Competitors
    • 4.4.8.4 Target Customers
    • 4.4.8.5 Analyst View
  • 4.4.9 PathAI
    • 4.4.9.1 Overview
    • 4.4.9.2 Top Products/Services
    • 4.4.9.3 Top Competitors
    • 4.4.9.4 Target Customers
    • 4.4.9.5 Analyst View

5 Research Methodology

• 5.1 Data Sources
  • 5.1.1 Primary Data Sources
  • 5.1.2 Secondary Data Sources
  • 5.1.3 Data Triangulation
• 5.2 Market Estimation and Forecast

List of Figures

• Figure 1: U.S. AI in healthcare Market (by Offering), $Billion, 2023 and 2034
• Figure 2: U.S. AI in healthcare Market (by End User), $Billion, 2023 and 2034
• Figure 3: Key Events to Keep Track of in the U.S. AI in Healthcare Market
• Figure 4: AI Adoption Vs. Market Readiness Across Healthcare Applications
• Figure 5: Share of Strategic Initiatives, January 2019-December 2023
• Figure 6: Strategic Initiatives (by Year), January 2019-December 2023
• Figure 7: Partnerships, Alliances, and Business Expansions, January 2019-December 2023
• Figure 8: Funding Activities, January 2019-December 2023
• Figure 9: Merger and Acquisition, January 2019-December 2023
• Figure 10: New Offerings and Regulatory Approval, January 2019-December 2023
• Figure 11: Data Triangulation
• Figure 12: Top-Down and Bottom-Up Approach
• Figure 13: Assumptions and Limitations

List of Tables

• Table 1: Market Snapshot
• Table 2: Impact Analysis of U.S. AI in Healthcare Market Navigating Factors, 2024-2034
• Table 3: U.S. AI in Healthcare Market (by Offering), $Billion, 2023-2034
• Table 4: U.S. AI in Healthcare Market (by End User), $Billion, 2023-2034