헬스케어 분야 에이전트 AI 시장 규모, 점유율, 동향 분석 보고서 : 에이전트 시스템별, 기술별, 제품별, 용도별, 최종 용도별, 지역별, 부문 예측(2025-2030년)

Agentic AI In Healthcare Market Growth & Trends:

The global agentic AI in healthcare market size is anticipated to reach USD 4.96 billion by 2030 and is projected to grow at a CAGR of 45.56% from 2025 to 2030, according to a new report by Grand View Research, Inc. Growing focus on personalized treatments, increasing shift to proactive care promoting better health outcomes, rising need for diagnostic accuracy, and growing focus on cost reduction are some of the factors contributing to market growth.

AI agents enable personalized medicine by analyzing patient history and real-time metrics. Remote monitoring through wearables alerts providers to potential emergencies. Moreover, AI agents drive cardiology, radiology, neurology, and dermatology advancements. These tools analyze ECGs, automate imaging diagnostics, and monitor EEGs, driving improvements in precision diagnostics and innovative research.

In addition, they analyze large volumes of medical data, such as medical imaging, genetic information, and patient history, to detect patterns that may be missed by human doctors. For instance, in February 2025, Thoughtful AI partnered with Hopebridge Autism Therapy Centers to enhance autism care through advanced AI technology. This collaboration aims to improve patient outcomes by utilizing AI-driven insights and tools, enabling therapists to provide more personalized and effective treatment plans for children with autism.

Furthermore, the integration of Agentic AI into healthcare revenue cycle management (RCM) is driving significant transformation in the healthcare industry, enhancing both financial performance and operational efficiency. AI agents in revenue cycle management assist by automating medical billing and coding, ensuring that claims are submitted quickly and accurately. These AI tools analyze medical records and automatically assign the correct codes, reducing errors that often lead to claim denials. AI agents effectively enhance patient interactions by delivering transparent billing information, sending reminders, and providing support through chatbots or virtual assistants. They also assist patients in navigating insurance coverage, payment options, and financial assistance programs, thereby improving patient satisfaction and expediting payments.

Agentic AI In Healthcare Market Report Highlights:

• Based on agent system, the single agent systems dominated the market in terms of revenue in 2024, as these systems operate independently without needing to coordinate with other agents.
• Based on product, the ready-to-deploy agents segment dominated the market with the largest revenue share in 2024, as these agents allow organizations to implement solutions quickly without the need for extensive customization or development time.
• Based on technology, the machine learning segment held the largest revenue share in 2024. Moreover, the context-aware computing segment is expected to grow at the fastest CAGR during the forecast period.
• Based on application, the medical imaging segment held the largest revenue share in 2024, as AI agents analyze vast amounts of imaging data quickly and with high precision. For instance, they are able to identify patterns indicative of diseases such as cancer or cardiovascular conditions by comparing new images against extensive databases of previously analyzed cases.
• Based on end use, the healthcare companies segment dominated the market with the largest share in 2024, owing to the ability of AI agents to assist these companies in drug discovery & development, clinical trial design and management, regulatory compliance, pharmacovigilance, etc.
• North America region held the largest market share in 2024, owing to the presence of major market players, widespread adoption of artificial intelligence in healthcare, and technological advancements.
• In September 2024, Thoughtful AI launched PAULA, an AI Agent that automates prior authorization processes in healthcare revenue cycle management. PAULA significantly reduces administrative time by 80% and boasts a 98% first-pass resolution rate, streamlining submissions, tracking, and appeals. This ultimately enhances patient care and improves provider claims approval rates.

Table of Contents

Chapter 1. Methodology and Scope

• 1.1. Market Segmentation & Scope
• 1.2. Market Definitions
  • 1.2.1. Agent System
  • 1.2.2. Product Segment
  • 1.2.3. Technology Segment
  • 1.2.4. Application Segment
  • 1.2.5. End Use
• 1.3. Information analysis
  • 1.3.1. Market formulation & data visualization
• 1.4. Data validation & publishing
• 1.5. Information Procurement
  • 1.5.1. Primary Research
• 1.6. Information or Data Analysis
• 1.7. Market Formulation & Validation
• 1.8. Market Model
• 1.9. Total Market: CAGR Calculation
• 1.10. Objectives
  • 1.10.1. Objective 1
  • 1.10.2. Objective 2

Chapter 2. Executive Summary

• 2.1. Market Outlook
• 2.2. Segment Snapshot
• 2.3. Competitive Insights Landscape

Chapter 3. Agentic AI in Healthcare Market Variables, Trends & Scope

• 3.1. Market Lineage Outlook
  • 3.1.1. Parent market outlook
  • 3.1.2. Related/ancillary market outlook.
• 3.2. Market Dynamics
  • 3.2.1. Market driver analysis
    • 3.2.1.1. Rising demand for personalized healthcare solutions
    • 3.2.1.2. Growing integration of AI in disease diagnostics and rising shift towards preventive care
    • 3.2.1.3. Technological advancements in AI
  • 3.2.2. Market restraint analysis
    • 3.2.2.1. Data Security and privacy concerns
    • 3.2.2.2. High integration costs
  • 3.2.3. Market opportunity analysis
    • 3.2.3.1. AI in drug discovery and development
    • 3.2.3.2. Enhanced medical imaging and diagnostics
    • 3.2.3.3. Rise in remote monitoring and telemedicine
  • 3.2.4. Market challenges analysis
• 3.3. Agentic AI in Healthcare Market Analysis Tools
  • 3.3.1. Industry Analysis - Porter's
    • 3.3.1.1. Supplier power
    • 3.3.1.2. Buyer power
    • 3.3.1.3. Substitution threat
    • 3.3.1.4. Threat of new entrant
    • 3.3.1.5. Competitive rivalry
  • 3.3.2. PESTEL Analysis
    • 3.3.2.1. Political landscape
    • 3.3.2.2. Technological landscape
    • 3.3.2.3. Economic landscape
    • 3.3.2.4. Environmental Landscape
    • 3.3.2.5. Legal Landscape
    • 3.3.2.6. Social Landscape
• 3.4. Case Study
• 3.5. Adoption Trends by Technology

Chapter 4. Agentic AI in Healthcare Market: Agent Systems Estimates & Trend Analysis

• 4.1. Segment Dashboard
• 4.2. Global Agentic AI in Healthcare Market Agent Systems Movement Analysis
• 4.3. Global Agentic AI in Healthcare Market Size & Trend Analysis, by Agent Systems, 2018 to 2030 (USD Million)
• 4.4. Single Agent Systems
  • 4.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 4.5. Multi Agent Systems
  • 4.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 5. Agentic AI in Healthcare Market: Product Estimates & Trend Analysis

• 5.1. Segment Dashboard
• 5.2. Global Agentic AI in Healthcare Market Product Movement Analysis
• 5.3. Global Agentic AI in Healthcare Market Size & Trend Analysis, by Product, 2018 to 2030 (USD Million)
• 5.4. Ready-to-Deploy Agents
  • 5.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 5.5. Multi Agent Systems
  • 5.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 6. Agentic AI in Healthcare Market: Technology Estimates & Trend Analysis

• 6.1. Segment Dashboard
• 6.2. Global Agentic AI in Healthcare Market Technology Movement Analysis
• 6.3. Global Agentic AI in Healthcare Market Size & Trend Analysis, by Technology, 2018 to 2030 (USD Million)
• 6.4. Machine Learning
  • 6.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.4.2. Deep Learning
    • 6.4.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.4.3. Supervised
    • 6.4.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.4.4. Unsupervised
    • 6.4.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.4.5. Others
    • 6.4.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 6.5. Natural Language Processing
  • 6.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.2. Smart Assistance
    • 6.5.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.3. OCR (Optical Character Recognition)
    • 6.5.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.4. Auto Coding
    • 6.5.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.5. Text Analytics
    • 6.5.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.6. Speech Analytics
    • 6.5.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
  • 6.5.7. Classification & Categorization
    • 6.5.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 6.6. Context-aware Computing
  • 6.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 6.7. Computer Vision
  • 6.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 7. Agentic AI in Healthcare Market: Application Estimates & Trend Analysis

• 7.1. Segment Dashboard
• 7.2. Global Agentic AI in Healthcare Market Application Movement Analysis
• 7.3. Global Agentic AI in Healthcare Market Size & Trend Analysis, by Application, 2018 to 2030 (USD Million)
• 7.4. Medical Imaging
  • 7.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.5. Personalized Treatment & Drug Discovery
  • 7.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.6. Electronic Health Records (EHRs)
  • 7.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.7. Remote Patient Care
  • 7.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.8. Clinical Decision-Making
  • 7.8.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.9. Risk Prediction & Pandemic Preparedness
  • 7.9.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.10. Genomic Data Analysis
  • 7.10.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.11. Chronic Disease Management
  • 7.11.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.12. Hospital Resource Optimization
  • 7.12.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.13. Medical Research and Data analysis
  • 7.13.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 7.14. Others
  • 7.14.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 8. Agentic AI in Healthcare Market: End Use Estimates & Trend Analysis

• 8.1. Segment Dashboard
• 8.2. Global Agentic AI in Healthcare Market End Use Movement Analysis
• 8.3. Global Agentic AI in Healthcare Market Size & Trend Analysis, by End Use, 2018 to 2030 (USD Million)
• 8.4. Healthcare Providers
  • 8.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 8.5. Healthcare Companies
  • 8.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 8.6. Academic and Research Institutes
  • 8.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 8.7. Healthcare Payers
  • 8.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)
• 8.8. Others
  • 8.8.1. Market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 9. Agentic AI in Healthcare Market: Regional Estimates & Trend Analysis

• 9.1. Regional Market Share Analysis, 2024 & 2030
• 9.2. Regional Market Dashboard
• 9.3. Market Size & Forecasts Trend Analysis, 2018 to 2030
• 9.4. North America
  • 9.4.1. U.S.
    • 9.4.1.1. Key country dynamics
    • 9.4.1.2. Regulatory framework
    • 9.4.1.3. Competitive scenario
    • 9.4.1.4. U.S. market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.4.2. Canada
    • 9.4.2.1. Key country dynamics
    • 9.4.2.2. Regulatory framework
    • 9.4.2.3. Competitive scenario
    • 9.4.2.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.4.3. Mexico
    • 9.4.3.1. Key country dynamics
    • 9.4.3.2. Regulatory framework
    • 9.4.3.3. Competitive scenario
    • 9.4.3.4. Mexico market estimates and forecasts 2018 to 2030 (USD Million)
• 9.5. Europe
  • 9.5.1. UK
    • 9.5.1.1. Key country dynamics
    • 9.5.1.2. Regulatory framework
    • 9.5.1.3. Competitive scenario
    • 9.5.1.4. UK market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.5.2. Germany
    • 9.5.2.1. Key country dynamics
    • 9.5.2.2. Regulatory framework
    • 9.5.2.3. Competitive scenario
    • 9.5.2.4. Germany market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.5.3. France
    • 9.5.3.1. Key country dynamics
    • 9.5.3.2. Regulatory framework
    • 9.5.3.3. Competitive scenario
    • 9.5.3.4. France market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.5.4. Italy
    • 9.5.4.1. Key country dynamics
    • 9.5.4.2. Regulatory framework
    • 9.5.4.3. Competitive scenario
    • 9.5.4.4. Italy market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.5.5. Spain
    • 9.5.5.1. Key country dynamics
    • 9.5.5.2. Regulatory framework
    • 9.5.5.3. Competitive scenario
    • 9.5.5.4. Spain market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.5.6. Norway
    • 9.5.6.1. Key country dynamics
    • 9.5.6.2. Regulatory framework
    • 9.5.6.3. Competitive scenario
    • 9.5.6.4. Norway market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.5.7. Sweden
    • 9.5.7.1. Key country dynamics
    • 9.5.7.2. Regulatory framework
    • 9.5.7.3. Competitive scenario
    • 9.5.7.4. Sweden market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.5.8. Denmark
    • 9.5.8.1. Key country dynamics
    • 9.5.8.2. Regulatory framework
    • 9.5.8.3. Competitive scenario
    • 9.5.8.4. Denmark market estimates and forecasts 2018 to 2030 (USD Million)
• 9.6. Asia Pacific
  • 9.6.1. Japan
    • 9.6.1.1. Key country dynamics
    • 9.6.1.2. Regulatory framework
    • 9.6.1.3. Competitive scenario
    • 9.6.1.4. Japan market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.6.2. China
    • 9.6.2.1. Key country dynamics
    • 9.6.2.2. Regulatory framework
    • 9.6.2.3. Competitive scenario
    • 9.6.2.4. China market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.6.3. India
    • 9.6.3.1. Key country dynamics
    • 9.6.3.2. Regulatory framework
    • 9.6.3.3. Competitive scenario
    • 9.6.3.4. India market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.6.4. Australia
    • 9.6.4.1. Key country dynamics
    • 9.6.4.2. Regulatory framework
    • 9.6.4.3. Competitive scenario
    • 9.6.4.4. Australia market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.6.5. South Korea
    • 9.6.5.1. Key country dynamics
    • 9.6.5.2. Regulatory framework
    • 9.6.5.3. Competitive scenario
    • 9.6.5.4. South Korea market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.6.6. Thailand
    • 9.6.6.1. Key country dynamics
    • 9.6.6.2. Regulatory framework
    • 9.6.6.3. Competitive scenario
    • 9.6.6.4. Thailand market estimates and forecasts 2018 to 2030 (USD Million)
• 9.7. Latin America
  • 9.7.1. Brazil
    • 9.7.1.1. Key country dynamics
    • 9.7.1.2. Regulatory framework
    • 9.7.1.3. Competitive scenario
    • 9.7.1.4. Brazil market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.7.2. Argentina
    • 9.7.2.1. Key country dynamics
    • 9.7.2.2. Regulatory framework
    • 9.7.2.3. Competitive scenario
    • 9.7.2.4. Argentina market estimates and forecasts 2018 to 2030 (USD Million)
• 9.8. MEA
  • 9.8.1. South Africa
    • 9.8.1.1. Key country dynamics
    • 9.8.1.2. Regulatory framework
    • 9.8.1.3. Competitive scenario
    • 9.8.1.4. South Africa market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.8.2. Saudi Arabia
    • 9.8.2.1. Key country dynamics
    • 9.8.2.2. Regulatory framework
    • 9.8.2.3. Competitive scenario
    • 9.8.2.4. Saudi Arabia market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.8.3. UAE
    • 9.8.3.1. Key country dynamics
    • 9.8.3.2. Regulatory framework
    • 9.8.3.3. Competitive scenario
    • 9.8.3.4. UAE market estimates and forecasts 2018 to 2030 (USD Million)
  • 9.8.4. Kuwait
    • 9.8.4.1. Key country dynamics
    • 9.8.4.2. Regulatory framework
    • 9.8.4.3. Competitive scenario
    • 9.8.4.4. Kuwait market estimates and forecasts 2018 to 2030 (USD Million)

Chapter 10. Competitive Landscape

• 10.1. Company/Competition Categorization
• 10.2. Strategy Mapping
• 10.3. Company Market Position Analysis, 2024
• 10.4. Company Profiles/Listing
  • 10.4.1. nVIDIA
    • 10.4.1.1. Company overview
    • 10.4.1.2. Financial performance
    • 10.4.1.3. Technology type benchmarking
    • 10.4.1.4. Strategic initiatives
  • 10.4.2. Oracle
    • 10.4.2.1. Company overview
    • 10.4.2.2. Financial performance
    • 10.4.2.3. Technology type benchmarking
    • 10.4.2.4. Strategic initiatives
  • 10.4.3. GE Healthcare
    • 10.4.3.1. Company overview
    • 10.4.3.2. Financial performance
    • 10.4.3.3. Technology type benchmarking
    • 10.4.3.4. Strategic initiatives
  • 10.4.4. Thoughtful Automation Inc.
    • 10.4.4.1. Company overview
    • 10.4.4.2. Financial performance
    • 10.4.4.3. Technology type benchmarking
    • 10.4.4.4. Strategic initiatives
  • 10.4.5. Hippocratic AI Inc.
    • 10.4.5.1. Company overview
    • 10.4.5.2. Financial performance
    • 10.4.5.3. Technology type benchmarking
    • 10.4.5.4. Strategic initiatives
  • 10.4.6. Cognigy
    • 10.4.6.1. Company overview
    • 10.4.6.2. Financial performance
    • 10.4.6.3. Technology type benchmarking
    • 10.4.6.4. Strategic initiatives
  • 10.4.7. Amelia US LLC
    • 10.4.7.1. Company overview
    • 10.4.7.2. Financial performance
    • 10.4.7.3. Technology type benchmarking
    • 10.4.7.4. Strategic initiatives
  • 10.4.8. Beam AI.
    • 10.4.8.1. Company overview
    • 10.4.8.2. Financial performance
    • 10.4.8.3. Technology type benchmarking
    • 10.4.8.4. Strategic initiatives
  • 10.4.9. Momentum.
    • 10.4.9.1. Company overview
    • 10.4.9.2. Financial performance
    • 10.4.9.3. Technology type benchmarking
    • 10.4.9.4. Strategic initiatives
  • 10.4.10. Notable
    • 10.4.10.1. Company overview
    • 10.4.10.2. Financial performance
    • 10.4.10.3. Technology type benchmarking
    • 10.4.10.4. Strategic initiatives
  • 10.4.11. Springs
    • 10.4.11.1. Company overview
    • 10.4.11.2. Financial performance
    • 10.4.11.3. Technology type benchmarking
    • 10.4.11.4. Strategic initiatives