세계의 의료 분야 생성형 AI 시장 예측(-2032년) : 솔루션 유형별, 규제 영역별, 전개 방식별, 조직 규모별, 최종 사용자별, 지역별 분석

According to Stratistics MRC, the Global Generative AI in Healthcare Market is accounted for $2.8 billion in 2025 and is expected to reach $20.1 billion by 2032 growing at a CAGR of 32.1% during the forecast period. Generative AI in healthcare refers to advanced artificial intelligence systems that create new content, insights, or solutions by learning patterns from vast medical data. These AI models can generate synthetic medical images, simulate patient outcomes, design personalized treatment plans, and assist in drug discovery. By analyzing electronic health records, genomics, and clinical research, generative AI supports predictive diagnostics, precision medicine, and medical education. Its capabilities enhance decision-making, accelerate research, and reduce costs, while ensuring improved patient care and innovation across the healthcare ecosystem.

Market Dynamics:

Driver:

Operational efficiency and cost reduction

Hospitals and insurers are deploying AI to automate documentation, streamline diagnostics, and reduce administrative overhead. Generative models are improving clinical decision support and patient engagement through synthetic data and personalized content. Integration with EHRs and workflow tools is enhancing usability and speed. Providers are using AI to optimize resource allocation and reduce burnout. These efficiencies are propelling large-scale implementation across care delivery.

Restraint:

Bias and fairness issues

Models trained on non-representative datasets can produce skewed outputs that affect diagnosis and treatment. Lack of transparency in model logic complicates validation and oversight. Disparities in outcomes may reinforce systemic inequities across patient populations. Developers face scrutiny from regulators and ethics boards. These risks continue to constrain adoption in high-stakes applications.

Opportunity:

Advancements in clinical trials

AI is generating synthetic control arms and simulating trial outcomes to reduce time and cost. Natural language models are automating protocol design and eligibility screening. Integration with real-world data is improving trial diversity and predictive accuracy. Sponsors are using AI to optimize site selection and patient engagement. These innovations are fostering transformation in clinical research.

Threat:

Resistance to adoption among healthcare professionals

Concerns about accuracy, liability, and job displacement are slowing acceptance. Many clinicians lack training to interpret or validate AI-generated outputs. Trust in black-box systems remains low without explainability and oversight. Misalignment between AI tools and clinical routines reduces usability. These barriers continue to hamper frontline adoption.

Covid-19 Impact:

The pandemic accelerated interest in generative AI as healthcare systems faced resource constraints and data gaps. AI was used to simulate disease spread, generate synthetic datasets, and support remote diagnostics. Emergency use cases validated the speed and adaptability of generative models. Providers adopted AI to manage documentation, triage, and patient communication during surges. Post-pandemic strategies now include AI as a core component of digital resilience. These shifts are accelerating long-term investment in generative healthcare tools.

The risk & compliance management segment is expected to be the largest during the forecast period

The risk & compliance management segment is expected to account for the largest market share during the forecast period due to its critical role in documentation, audit readiness, and regulatory reporting. Generative AI is automating policy generation, incident summaries, and compliance workflows. Hospitals and insurers are using AI to detect anomalies and generate audit trails. Integration with governance platforms is improving traceability and response time. Demand for scalable, real-time compliance tools is rising across payers and providers. These capabilities are boosting segment dominance in enterprise healthcare.

The fintech platforms segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the fintech platforms segment is predicted to witness the highest growth rate as digital health financing and insurance models adopt generative AI. AI is generating personalized coverage summaries, fraud detection narratives, and claims explanations. Startups are embedding generative tools into health wallets and benefit navigation apps. Integration with APIs and open banking systems is expanding functionality. Demand for transparency and automation in health finance is rising across demographics.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its advanced healthcare infrastructure, AI investment, and regulatory engagement. The United States is scaling generative AI across hospitals, insurers, and research institutions. Investment in cloud platforms and data interoperability is driving deployment. Presence of leading AI vendors and academic centers is reinforcing innovation. Regulatory frameworks are evolving to support responsible AI in clinical settings. These factors are boosting regional leadership in generative healthcare applications. Matter for Asia Pacific?

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR as healthcare digitization, AI investment, and policy support converge. Countries like India, China, Japan, and South Korea are scaling generative AI across diagnostics, insurance, and clinical research. Local startups are launching multilingual tools tailored to regional health systems and patient needs. Governments are funding AI integration in public hospitals and medical education. Demand for scalable, low-cost automation is rising across urban and rural care settings.

Key players in the market

Some of the key players in Generative AI in Healthcare Market include IBM Corporation, Microsoft Corporation, Google LLC, Amazon Web Services, Inc., NVIDIA Corporation, Oracle Corporation, Salesforce, Inc., Tempus Labs, Inc., Insilico Medicine, Inc., PathAI, Inc., Suki AI, Inc., Athelas, Inc., K Health, Inc., Hippocratic AI, Inc. and Corti.ai ApS.

Key Developments:

In May 2025, Microsoft deepened its healthcare partnerships through Microsoft Cloud for Healthcare, integrating generative AI into clinical documentation, diagnostics, and patient engagement. Collaborations with Epic Systems and Nuance enabled real-time chart summarization and ambient clinical intelligence, helping reduce physician burnout and improve care delivery.

In December 2024, IBM announced expanded partnerships across its AI Ecosystem, enabling healthcare enterprises to move generative AI projects from pilot to production. These collaborations focus on responsible scaling, integrating IBM's enterprise-grade AI with partner expertise to modernize diagnostics, patient engagement, and clinical workflows.

Solution Types Covered:

• Risk & Compliance Management
• Regulatory Reporting Automation
• Identity Verification & KYC
• Anti-Money Laundering (AML) Solutions
• Transaction Monitoring
• Fraud Detection & Prevention
• Data Governance & Privacy Management
• Audit Trail & Recordkeeping
• Other Solution Types

Regulatory Domain s Covered:

• Financial Services Compliance
• Data Protection & Privacy (GDPR, CCPA, etc.)
• Tax & Accounting Compliance
• Environmental, Social & Governance (ESG)
• Other Regulatory Domains

Deployment Modes Covered:

• Cloud-Based
• On-Premise
• Hybrid

Organization Sizes Covered:

• Small & Medium Enterprises (SMEs)
• Large Enterprises

End Users Covered:

• Banks & Financial Institutions
• Insurance Companies
• Fintech Platforms
• Legal & Consulting Firms
• Healthcare Providers
• Other End Users

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 End User Analysis
• 3.7 Emerging Markets
• 3.8 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global Generative AI in Healthcare Market, By Solution Type

• 5.1 Introduction
• 5.2 Risk & Compliance Management
• 5.3 Regulatory Reporting Automation
• 5.4 Identity Verification & KYC
• 5.5 Anti-Money Laundering (AML) Solutions
• 5.6 Transaction Monitoring
• 5.7 Fraud Detection & Prevention
• 5.8 Data Governance & Privacy Management
• 5.9 Audit Trail & Recordkeeping
• 5.10 Other Solution Types

6 Global Generative AI in Healthcare Market, By Regulatory Domain

• 6.1 Introduction
• 6.2 Financial Services Compliance
• 6.3 Data Protection & Privacy (GDPR, CCPA, etc.)
• 6.4 Tax & Accounting Compliance
• 6.5 Environmental, Social & Governance (ESG)
• 6.6 Other Regulatory Domains

7 Global Generative AI in Healthcare Market, By Deployment Mode

• 7.1 Introduction
• 7.2 Cloud-Based
• 7.3 On-Premise
• 7.4 Hybrid

8 Global Generative AI in Healthcare Market, By Organization Size

• 8.1 Introduction
• 8.2 Small & Medium Enterprises (SMEs)
• 8.3 Large Enterprises

9 Global Generative AI in Healthcare Market, By End User

• 9.1 Introduction
• 9.2 Banks & Financial Institutions
• 9.3 Insurance Companies
• 9.4 Fintech Platforms
• 9.5 Legal & Consulting Firms
• 9.6 Healthcare Providers
• 9.7 Other End Users

10 Global Generative AI in Healthcare Market, By Geography

• 10.1 Introduction
• 10.2 North America
  • 10.2.1 US
  • 10.2.2 Canada
  • 10.2.3 Mexico
• 10.3 Europe
  • 10.3.1 Germany
  • 10.3.2 UK
  • 10.3.3 Italy
  • 10.3.4 France
  • 10.3.5 Spain
  • 10.3.6 Rest of Europe
• 10.4 Asia Pacific
  • 10.4.1 Japan
  • 10.4.2 China
  • 10.4.3 India
  • 10.4.4 Australia
  • 10.4.5 New Zealand
  • 10.4.6 South Korea
  • 10.4.7 Rest of Asia Pacific
• 10.5 South America
  • 10.5.1 Argentina
  • 10.5.2 Brazil
  • 10.5.3 Chile
  • 10.5.4 Rest of South America
• 10.6 Middle East & Africa
  • 10.6.1 Saudi Arabia
  • 10.6.2 UAE
  • 10.6.3 Qatar
  • 10.6.4 South Africa
  • 10.6.5 Rest of Middle East & Africa

11 Key Developments

• 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 11.2 Acquisitions & Mergers
• 11.3 New Product Launch
• 11.4 Expansions
• 11.5 Other Key Strategies

12 Company Profiling

• 12.1 IBM Corporation
• 12.2 Microsoft Corporation
• 12.3 Google LLC
• 12.4 Amazon Web Services, Inc.
• 12.5 NVIDIA Corporation
• 12.6 Oracle Corporation
• 12.7 Salesforce, Inc.
• 12.8 Tempus Labs, Inc.
• 12.9 Insilico Medicine, Inc.
• 12.10 PathAI, Inc.
• 12.11 Suki AI, Inc.
• 12.12 Athelas, Inc.
• 12.13 K Health, Inc.
• 12.14 Hippocratic AI, Inc.
• 12.15 Corti.ai ApS