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Report
United States AI in Healthcare Market By Component (Hardware, Software, Services), By Application (Robot-assisted Surgery, Virtual Assistants, Administrative Workflow Assistants, Connected Medical Devices, Medical Imaging & Diagnostics, Clinical Trials, Cybersecurity, Precision Medicine, Drug Discovery & Development, Wearables, Others), By Technology (Machine Learning, Natural Language Processing, Context-aware Computing, Computer Vision), By End User (Healthcare Providers, Healthcare Payers, Healthcare Companies, Patients, Others), By Region, Competition, Forecast & Opportunities, 2020-2030F
Market Report I 2025-04-25 I 82 Pages I TechSci Research
Market Overview
The U.S. AI in Healthcare Market was valued at USD 10.82 billion in 2024 and is expected to reach USD 85.84 billion by 2030, expanding at a robust CAGR of 41.20% during the forecast period. This significant growth is attributed to rapid technological advancements, evolving patient expectations, and the pressing need to enhance clinical productivity. AI is being deployed across a broad spectrum of healthcare applications, including diagnostic imaging, robotic surgeries, predictive analytics, and drug discovery. The increasing burden of chronic diseases, an aging demographic, and healthcare workforce shortages are prompting the adoption of AI-based solutions that streamline operations while sustaining high care standards. AI technologies are increasingly utilized to assist with real-time clinical decision-making, reduce diagnostic errors, and automate administrative functions. Further fueling adoption is the surge in public and private investments, along with a rising number of FDA-approved AI-powered medical devices, solidifying AI's role in modern healthcare delivery.
Key Market Drivers
Growing Demand for Efficient Healthcare Delivery
The escalating demand for more efficient healthcare delivery systems is a major catalyst for AI adoption in the U.S. healthcare market. Rising patient loads, resource constraints, and the increasing prevalence of chronic illnesses have made it imperative to find technologies that enhance clinical productivity without compromising care quality. AI-driven tools such as predictive analytics platforms, automated scheduling systems, and clinical decision support solutions are enabling hospitals and providers to reduce operational bottlenecks, improve patient flow, and accelerate diagnostics-ultimately enhancing care coordination and reducing healthcare costs.
Key Market Challenges
Data Privacy and Security Concerns
The widespread integration of AI into healthcare workflows introduces significant data privacy and security risks, which remain a pressing concern. The deployment of AI solutions depends heavily on access to sensitive patient data-including electronic health records, genetic data, and real-time monitoring feeds-which are vulnerable to cyberattacks. The expanding digital footprint through cloud computing, EHRs, and AI-enabled wearables increases the threat landscape. Inconsistent cybersecurity standards and data-sharing protocols across stakeholders complicate secure implementation. High-profile data breaches have raised alarm among healthcare providers and patients, highlighting the need for stringent data governance and robust security frameworks.
Key Market Trends
Integration of AI with Electronic Health Records (EHRs)
The integration of AI into electronic health record systems is transforming healthcare operations by automating documentation, streamlining workflows, and enhancing decision-making. AI technologies, especially natural language processing (NLP), are being embedded into EHR platforms to perform functions such as transcription, coding, and structured data extraction from unstructured inputs. These integrations help clinicians spend less time on administrative tasks and more on patient engagement. For example, startups like Abridge are leveraging AI to convert clinician-patient conversations into clinical notes, while Suki offers AI assistants that integrate directly with EHRs to simplify routine documentation. Such innovations are boosting efficiency, reducing burnout, and improving overall care delivery.
Key Market Players
- Microsoft
- NVIDIA Corporation
- Epic Systems Corporation
- GE Healthcare
- Medtronic
- Oracle
- Veradigm LLC
- Google
- Cognizant
- Amazon Web Services, Inc.
Report Scope:
In this report, the United States AI in Healthcare Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
- United States AI in Healthcare Market, By Component:
o Hardware
o Software
o Services
- United States AI in Healthcare Market, By Application:
o Robot-assisted Surgery
o Virtual Assistants
o Administrative Workflow Assistants
o Connected Medical Devices
o Medical Imaging & Diagnostics
o Clinical Trials
o Cybersecurity
o Precision Medicine
o Drug Discovery & Development
o Wearables
o Others
- United States AI in Healthcare Market, By Technology:
o Machine Learning
o Natural Language Processing
o Context-aware Computing
o Computer Vision
- United States AI in Healthcare Market, By End User:
o Healthcare Providers
o Healthcare Payers
o Healthcare Companies
o Patients
o Others
- United States AI in Healthcare Market, By Region:
o North-East
o Mid-West
o West
o South
Competitive Landscape
Company Profiles: Detailed analysis of the major companies present in the United States AI in Healthcare Market.
Available Customizations:
United States AI in Healthcare Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:
Company Information
- Detailed analysis and profiling of additional market players (up to five).
1. Product Overview
1.1. Market Definition
1.2. Scope of the Market
1.2.1. Markets Covered
1.2.2. Years Considered for Study
1.2.3. Key Market Segmentations
2. Research Methodology
2.1. Objective of the Study
2.2. Baseline Methodology
2.3. Key Industry Partners
2.4. Major Association and Secondary Sources
2.5. Forecasting Methodology
2.6. Data Triangulation & Validation
2.7. Assumptions and Limitations
3. Executive Summary
3.1. Overview of the Market
3.2. Overview of Key Market Segmentations
3.3. Overview of Key Market Players
3.4. Overview of Key Regions/Countries
3.5. Overview of Market Drivers, Challenges, Trends
4. Voice of Customer
5. United States AI in Healthcare Market Outlook
5.1. Market Size & Forecast
5.1.1. By Value
5.2. Market Share & Forecast
5.2.1. By Component (Hardware, Software, Services)
5.2.2. By Application (Robot-assisted Surgery, Virtual Assistants, Administrative Workflow Assistants, Connected Medical Devices, Medical Imaging & Diagnostics, Clinical Trials, Cybersecurity, Precision Medicine, Drug Discovery & Development, Wearables, Others)
5.2.3. By Technology (Machine Learning, Natural Language Processing, Context-aware Computing, Computer Vision)
5.2.4. By End User (Healthcare Providers, Healthcare Payers, Healthcare Companies, Patients, Others)
5.2.5. By Region
5.2.6. By Company (2024)
5.3. Market Map
6. North-East AI in Healthcare Market Outlook
6.1. Market Size & Forecast
6.1.1. By Value
6.2. Market Share & Forecast
6.2.1. By Component
6.2.2. By Application
6.2.3. By Technology
6.2.4. By End User
7. Mid-West AI in Healthcare Market Outlook
7.1. Market Size & Forecast
7.1.1. By Value
7.2. Market Share & Forecast
7.2.1. By Component
7.2.2. By Application
7.2.3. By Technology
7.2.4. By End User
8. West AI in Healthcare Market Outlook
8.1. Market Size & Forecast
8.1.1. By Value
8.2. Market Share & Forecast
8.2.1. By Component
8.2.2. By Application
8.2.3. By Technology
8.2.4. By End User
9. South AI in Healthcare Market Outlook
9.1. Market Size & Forecast
9.1.1. By Value
9.2. Market Share & Forecast
9.2.1. By Component
9.2.2. By Application
9.2.3. By Technology
9.2.4. By End User
10. Market Dynamics
10.1. Drivers
10.2. Challenges
11. Market Trends & Developments
11.1. Merger & Acquisition (If Any)
11.2. Product Launches (If Any)
11.3. Recent Developments
12. Policy & Regulatory Landscape
13. United States Economic Profile
14. United States AI in Healthcare Market: SWOT Analysis
15. Porter's Five Forces Analysis
15.1. Competition in the Industry
15.2. Potential of New Entrants
15.3. Power of Suppliers
15.4. Power of Customers
15.5. Threat of Substitute Products
16. Competitive Landscape
16.1. Microsoft
16.1.1. Business Overview
16.1.2. Company Snapshot
16.1.3. Products & Services
16.1.4. Financials (As Reported)
16.1.5. Recent Developments
16.1.6. Key Personnel Details
16.1.7. SWOT Analysis
16.2. NVIDIA Corporation
16.3. Epic Systems Corporation
16.4. GE Healthcare
16.5. Medtronic
16.6. Oracle
16.7. Veradigm LLC
16.8. Google
16.9. Cognizant
16.10. Amazon Web Services, Inc.
17. Strategic Recommendations
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