Agentic AI In Healthcare Market Size, Share & Trends Analysis Report By Agent System (Single Agent Systems, Multi Agent Systems), By Technology (Machine Learning, NLP), By Product, By Application, By End-use, By Region, And Segment Forecasts, 2025 - 2030
This report can be delivered to the clients within 3 Business Days
Agentic AI In Healthcare Market Growth & Trends
The global agentic AI in healthcare market size is anticipated treach USD 4.96 billion by 2030 and is projected tgrow at a CAGR of 45.56% from 2025 t2030, according ta new report by Grand View Research, Inc. Growing focus on personalized treatments, increasing shift tproactive care promoting better health outcomes, rising need for diagnostic accuracy, and growing focus on cost reduction are some of the factors contributing tmarket growth.
AI agents enable personalized medicine by analyzing patient history and real-time metrics. Remote monitoring through wearables alerts providers tpotential 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, tdetect patterns that may be missed by human doctors. For instance, in February 2025, Thoughtful AI partnered with Hopebridge Autism Therapy Centers tenhance autism care through advanced AI technology. This collaboration aims timprove patient outcomes by utilizing AI-driven insights and tools, enabling therapists tprovide more personalized and effective treatment plans for children with autism.
Furthermore, the integration of Agentic AI inthealthcare 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 tclaim denials. AI agents effectively enhance patient interactions by delivering transparent billing information, sending reminders, and providing support through chatbots or virtual assistants. They alsassist 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
Agentic AI In Healthcare Market Growth & Trends
The global agentic AI in healthcare market size is anticipated treach USD 4.96 billion by 2030 and is projected tgrow at a CAGR of 45.56% from 2025 t2030, according ta new report by Grand View Research, Inc. Growing focus on personalized treatments, increasing shift tproactive care promoting better health outcomes, rising need for diagnostic accuracy, and growing focus on cost reduction are some of the factors contributing tmarket growth.
AI agents enable personalized medicine by analyzing patient history and real-time metrics. Remote monitoring through wearables alerts providers tpotential 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, tdetect patterns that may be missed by human doctors. For instance, in February 2025, Thoughtful AI partnered with Hopebridge Autism Therapy Centers tenhance autism care through advanced AI technology. This collaboration aims timprove patient outcomes by utilizing AI-driven insights and tools, enabling therapists tprovide more personalized and effective treatment plans for children with autism.
Furthermore, the integration of Agentic AI inthealthcare 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 tclaim denials. AI agents effectively enhance patient interactions by delivering transparent billing information, sending reminders, and providing support through chatbots or virtual assistants. They alsassist 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 tcoordinate 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 timplement 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 tgrow 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 tidentify 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 tthe ability of AI agents tassist 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 tthe 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.
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
1.10.2. Objective
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
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
1.10.2. Objective
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
