일본의 헬스케어 분야 AI 시장(2025-2033년)

The Japan AI in healthcare market reached US$ 1.42 billion in 2024 and is expected to reach US$ 14.8 billion by 2033, growing at a CAGR of 36.5% during the forecast period 2025-2033.

Japan's AI in the healthcare market is transforming the healthcare sector by leveraging artificial intelligence (AI) technologies to enhance diagnostics, treatment planning, drug development, and patient management systems. AI analyzes medical images such as X-rays, CT scans, and MRI scans to improve diagnostic accuracy and speed. Companies like LPixel and Fujifilm Corporation are leading in this area, with AI algorithms capable of detecting abnormalities that may not be visible to the human eye.

AI helps in the early detection of cancers by identifying patterns in medical images, significantly improving diagnostic outcomes. AI can predict disease progression and aid in preventive medicine by analyzing patient data and medical histories. This predictive capability helps healthcare providers take proactive measures to manage chronic conditions and aids in tailoring treatments to individual patients based on genetic profiles and medical histories, enhancing treatment effectiveness and patient outcomes.

Market Dynamics: Drivers & Restraints

Technological Advancements

The technological advancements are expected to drive the growth of Japan's AI in the healthcare market in the forecast period. Japan's AI healthcare start-up scene is rapidly growing, with new tools aimed at improving diagnostic speed and accuracy for diseases like cancer, influenza, and heart disease. However, integrating these AI tools faces challenges, such as a lengthy approval process for new products. Despite these hurdles, global efforts to manage ethical risks and set standards are expected to help overcome barriers, facilitating AI's role in enhancing Japan's healthcare system.

AI integration in Japan's healthcare sector is transforming diagnostic and treatment processes. Key areas include medical imaging for improved accuracy in detecting diseases like cancer, predictive analytics to personalize treatments and predict disease progression, and healthcare robotics for assisting surgeries and nursing support. These technologies address challenges like Japan's aging population and labor shortages. Growth drivers include advancements in AI, government support, and the market's potential, with forecasts showing significant expansion by 2027. AI is revolutionizing healthcare by enhancing precision, efficiency, and patient care outcomes.

Additionally, key players in the industry should launch innovative launches that would drive Japan's AI in the healthcare market growth. For instance, in November 2024, Japan is rapidly advancing in healthcare technology, focusing on next-generation drug design, healthcare robotics, and digital health platforms. Leveraging AI, the country aims to tackle various challenges, such as its aging population and shortage of healthcare workers, while improving the quality of medical care.

Also, in June 2024, SoftBank Group launched a joint venture with Tempus AI, named SB Tempus, aimed at transforming healthcare in Japan through AI-powered precision medicine. The partnership will utilize AI to analyze personal medical data, including genetic information, to offer personalized treatment plans. With an initial focus on oncology, this venture will help tailor targeted therapies, improving healthcare outcomes.

Data Privacy Concerns

Data privacy and regulatory challenges are major barriers to the integration of AI technologies into Japan's healthcare market. As AI becomes increasingly prevalent in areas like diagnostics, predictive analytics, and personalized medicine, it creates new risks surrounding the security and use of sensitive health data, including medical records, genetic data, and patient histories.

Japan's strict privacy laws, such as the Act on the Protection of Personal Information (APPI), impose significant requirements on healthcare providers to ensure patient data is secure and only shared with patient consent. However, AI systems often require vast amounts of data to function effectively, which raises concerns about data breaches, identity theft, and misuse of information. Thus, the above factors could be limiting Japan's AI in the healthcare market's potential growth.

Segment Analysis

The Japan AI in the healthcare market is segmented based on component, technology, application, and end-user.

Component:

The software solutions segment in the component is expected to dominate the Japan AI in the healthcare market share

The software solutions segment in Japan's AI in Healthcare market revolves around the development and deployment of AI-powered software designed to improve the efficiency, accuracy, and overall effectiveness of various healthcare functions, including diagnostics, treatment planning, and patient management. These solutions are pivotal in enhancing patient outcomes and streamlining healthcare processes.

AI-driven algorithms are used to enhance the analysis of medical images such as X-rays, CT scans, and MRIs, aiding in quicker and more precise diagnoses. Companies like LPixel and Fujifilm Corporation are at the forefront of applying AI to detect abnormalities, such as tumors or cardiovascular conditions. AI tools analyze vast amounts of patient data to predict potential diseases or health risks. By leveraging patient history, genetic information, and other medical records, these systems enable personalized treatment plans and early interventions, ultimately improving patient care outcomes.

Additionally, key players in the industry have innovative launches that would drive this segment growth in the Japan AI in healthcare market. For instance, in November 2023, RapidAI, a health tech company, received Class III Shonin clearance in Japan, allowing it to launch its Rapid Edge Cloud platform and a non-contrast CT tool for stroke identification. RapidAI's offerings include diagnostic solutions for stroke, aneurysms, and pulmonary embolisms. It also provides technology platforms for coordinated care between hospitals and EMS providers, analytics software for hospital operations, and a clinical trial platform to streamline screening and enrollment. These factors have solidified the segment's position in the Japanese AI in healthcare market.

Competitive Landscape

The major players in the Japan AI in healthcare market include IBM, FUJITSU, Microsoft, Cyberdyne Care Robotics GmbH, LPIXEL., Rakuten Group, Inc., MOLCURE Inc., Medmain Inc., and AI Medical Service Inc., among others.

Key Developments

• In November 2024, NVIDIA launched the BioNeMo framework to accelerate digital biology for the biopharma sector. This open-source platform is designed to help researchers in drug discovery and molecular design by scaling AI models for biomolecular research. The framework includes tools that enable the rapid development of large-scale models, such as AlphaFold2 for protein structure prediction and DiffDock 2.0 for faster and more accurate molecular docking predictions. The platform supports integration with existing high-performance computing systems, significantly enhancing research capabilities.

Why Purchase the Report?

• Pipeline & Innovations: Reviews ongoing clinical trials and product pipelines and forecasts upcoming advancements in medical devices and pharmaceuticals.
• Product Performance & Market Positioning: Analyze product performance, market positioning, and growth potential to optimize strategies.
• Real-World Evidence: Integrates patient feedback and data into product development for improved outcomes.
• Physician Preferences & Health System Impact: Examines healthcare provider behaviors and the impact of health system mergers on adoption strategies.
• Market Updates & Industry Changes: This covers recent regulatory changes, new policies, and emerging technologies.
• Competitive Strategies: Analyze competitor strategies, market share, and emerging players.
• Pricing & Market Access: Reviews pricing models, reimbursement trends, and market access strategies.
• Market Entry & Expansion: Identifies optimal strategies for entering new markets and partnerships.
• Regional Growth & Investment: Highlights high-growth regions and investment opportunities.
• Supply Chain Optimization: Assesses supply chain risks and distribution strategies for efficient product delivery.
• Sustainability & Regulatory Impact: Focuses on eco-friendly practices and evolving regulations in healthcare.
• Post-market Surveillance: Uses post-market data to enhance product safety and access.
• Pharmacoeconomics & Value-Based Pricing: Analyzes the shift to value-based pricing and data-driven decision-making in R&D.

The Japan AI in Healthcare Market report delivers a detailed analysis with 60+ key tables, more than 50 visually impactful figures, and 176 pages of expert insights, providing a complete view of the market landscape.

Target Audience 2024

• Manufacturers: Pharmaceutical, Medical Device, Biotech Companies, Contract Manufacturers, Distributors, Hospitals.
• Regulatory & Policy: Compliance Officers, Government, Health Economists, Market Access Specialists.
• Technology & Innovation: AI/Robotics Providers, R&D Professionals, Clinical Trial Managers, Pharmacovigilance Experts.
• Investors: Healthcare Investors, Venture Fund Investors, Pharma Marketing & Sales.
• Consulting & Advisory: Healthcare Consultants, Industry Associations, Analysts.
• Supply Chain: Distribution and Supply Chain Managers.
• Consumers & Advocacy: Patients, Advocacy Groups, Insurance Companies.
• Academic & Research: Academic Institutions.

Table of Contents

1. Market Introduction and Scope

• 1.1. Objectives of the Report
• 1.2. Report Coverage & Definitions
• 1.3. Report Scope

2. Executive Insights and Key Takeaways

• 2.1. Market Highlights and Strategic Takeaways
• 2.2. Key Trends and Future Projections
• 2.3. Snippet by Component
• 2.4. Snippet by Technology
• 2.5. Snippet by Application
• 2.6. Snippet by End-User

3. Dynamics

• 3.1. Impacting Factors
  • 3.1.1. Drivers
    • 3.1.1.1. Technological Advancements
    • 3.1.1.2. Rising Aging Population and Healthcare Needs
  • 3.1.2. Restraints
    • 3.1.2.1. Data Privacy Concerns
    • 3.1.2.2. Stringent Regulatory Environment
  • 3.1.3. Opportunity
    • 3.1.3.1. Investment in Precision Medicine
  • 3.1.4. Impact Analysis

4. Strategic Insights and Industry Outlook

• 4.1. Market Leaders and Pioneers
  • 4.1.1. Emerging Pioneers and Prominent Players
  • 4.1.2. Established leaders with largest-selling Brand
  • 4.1.3. Market leaders with established Product
• 4.2. CXO Perspectives
• 4.3. Latest Developments and Breakthroughs
• 4.4. Case Studies/Ongoing Research
• 4.5. Regulatory and Reimbursement Landscape
  • 4.5.1. North America
  • 4.5.2. Europe
  • 4.5.3. Asia Pacific
  • 4.5.4. Latin America
  • 4.5.5. Middle East & Africa
• 4.6. Porter's Five Forces Analysis
• 4.7. Supply Chain Analysis
• 4.8. Patent Analysis
• 4.9. SWOT Analysis
• 4.10. Unmet Needs and Gaps
• 4.11. Recommended Strategies for Market Entry and Expansion
• 4.12. Scenario Analysis: Best-Case, Base-Case, and Worst-Case Forecasts
• 4.13. Pricing Analysis and Price Dynamics
• 4.14. Key Opinion Leaders

5. Japan AI in Healthcare Market, By Component

• 5.1. Introduction
  • 5.1.1. Analysis and Y-o-Y Growth Analysis (%), By Component
  • 5.1.2. Market Attractiveness Index, By Component
• 5.2. Hardware*
  • 5.2.1. Introduction
  • 5.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 5.3. Software Solutions
• 5.4. Services

6. Japan AI in Healthcare Market, By Technology

• 6.1. Introduction
  • 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
  • 6.1.2. Market Attractiveness Index, By Technology
• 6.2. Machine Learning*
  • 6.2.1. Introduction
  • 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 6.3. Natural Language Processing
• 6.4. Context-Aware Computing
• 6.5. Computer Vision

7. Japan AI in Healthcare Market, By Application

• 7.1. Introduction
  • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
  • 7.1.2. Market Attractiveness Index, By Application
• 7.2. Critical Care*
  • 7.2.1. Introduction
  • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 7.3. Robot-Assisted Surgery
• 7.4. Virtual Nursing Assistants
• 7.5. Administrative Workflow Assistants
• 7.6. Fraud Detection
• 7.7. Cybersecurity
• 7.8. Dosage Error Reduction
• 7.9. Medical Diagnostics
• 7.10. Precision Medicine
• 7.11. Drug Discovery & Development
• 7.12. Remote Patient Monitoring
• 7.13. Wearables
• 7.14. Others

8. Japan AI in Healthcare Market, By End-User

• 8.1. Introduction
  • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
  • 8.1.2. Market Attractiveness Index, By End-User
• 8.2. Healthcare Providers*
  • 8.2.1. Introduction
  • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
• 8.3. Healthcare Payers
• 8.4. Healthcare Companies
• 8.5. Patients
• 8.6. Others

9. Competitive Landscape and Market Positioning

• 9.1. Competitive Overview and Key Market Players
• 9.2. Market Share Analysis and Positioning Matrix
• 9.3. Strategic Partnerships, Mergers & Acquisitions
• 9.4. Key Developments in Product Portfolios and Innovations
• 9.5. Company Benchmarking

10. Company Profiles

• 10.1. IBM *
  • 10.1.1. Company Overview
  • 10.1.2. Product Portfolio
    • 10.1.2.1. Product Description
    • 10.1.2.2. Product Key Performance Indicators (KPIs)
    • 10.1.2.3. Historic and Forecasted Product Sales
    • 10.1.2.4. Product Sales Volume
  • 10.1.3. Financial Overview
    • 10.1.3.1. Company Revenue's
    • 10.1.3.2. Geographical Revenue Shares
    • 10.1.3.3. Revenue Forecasts
  • 10.1.4. Key Developments
    • 10.1.4.1. Mergers & Acquisitions
    • 10.1.4.2. Key Product Development Activities
    • 10.1.4.3. Regulatory Approvals, etc.
  • 10.1.5. SWOT Analysis
• 10.2. FUJITSU
• 10.3. Microsoft
• 10.4. Cyberdyne Care Robotics GmbH
• 10.5. LPIXEL.
• 10.6. Rakuten Group, Inc.
• 10.7. MOLCURE Inc.
• 10.8. Medmain Inc.
• 10.9. AI Medical Service Inc.

LIST NOT EXHAUSTIVE

11. Assumption and Research Methodology

• 11.1. Data Collection Methods
• 11.2. Data Triangulation
• 11.3. Forecasting Techniques
• 11.4. Data Verification and Validation

12. Appendix

• 12.1. About Us and Services
• 12.2. Contact Us