정신건강 분야 인공지능(AI) 시장 : 규모, 점유율, 동향 및 성장 분석 보고서(2026-2034년)

The global artificial intelligence in mental health market size is expected to reach USD 14.55 Billion in 2034 from USD 2.19 Billion in 2025, growing at a CAGR of 23.42 during 2026-2034.The Artificial Intelligence in Mental Health Market is poised for transformative growth, driven by the increasing recognition of mental health issues and the need for innovative solutions. As mental health awareness rises globally, there is a growing demand for accessible and effective treatment options. AI technologies are being integrated into mental health care to enhance diagnostic accuracy, personalize treatment plans, and provide real-time support. By leveraging machine learning algorithms and natural language processing, AI can analyze vast amounts of data to identify patterns and predict mental health crises, enabling timely interventions that can significantly improve patient outcomes.

Moreover, the integration of AI in mental health applications is revolutionizing the way individuals access care. Telehealth platforms powered by AI are making mental health services more accessible, particularly in underserved areas where traditional resources may be limited. These platforms offer virtual therapy sessions, chatbots for immediate support, and self-help tools that empower individuals to manage their mental health proactively. As technology continues to evolve, the potential for AI to enhance the therapeutic experience and provide continuous support will likely drive further adoption in the mental health sector.

Additionally, ethical considerations and data privacy are becoming increasingly important in the Artificial Intelligence in Mental Health Market. As AI systems collect and analyze sensitive personal data, ensuring the security and confidentiality of this information is paramount. Stakeholders are focusing on developing robust frameworks that prioritize ethical AI practices, including transparency, accountability, and informed consent. As the market matures, addressing these challenges will be crucial for building trust among users and ensuring the responsible use of AI technologies in mental health care.

Our reports are carefully developed to deliver comprehensive and actionable insights across a wide range of industries and markets. Each report includes several essential components designed to provide a complete understanding of the market environment:

Market Overview: This section provides a clear introduction to the market, including key definitions, classifications, and an overview of the current industry landscape.

Market Dynamics: A detailed evaluation of the primary drivers, restraints, opportunities, and challenges shaping market growth. It covers factors such as technological developments, regulatory frameworks, and evolving industry trends.

Segmentation Analysis: A structured breakdown of the market into key segments based on product type, application, end-user, and geographic region. This section highlights the performance, growth potential, and contribution of each segment.

Competitive Landscape: An in-depth assessment of leading market participants, including their market positioning, product portfolios, strategic initiatives, and financial performance. It provides valuable insights into competitive dynamics and the strategies adopted by key players.

Market Forecast: Data-driven projections of market size and growth patterns over a defined forecast period. This section incorporates historical trends, current market conditions, and quantitative analysis to illustrate expected future developments.

Regional Analysis: A comprehensive review of market performance across major geographic regions, identifying high-growth areas and regional trends to better understand localized market opportunities.

Emerging Trends and Opportunities: Identification of significant market trends, technological advancements, and new investment opportunities. This section highlights potential growth areas and future industry developments.

Customization Options: We offer flexible customization services to tailor reports according to specific client requirements. This may include additional segmentation, country-level analysis, competitor profiling, customized data points, or focused insights on particular market segments to better support strategic decision-making.

MARKET SEGMENTATION

By Component

• Software-as-a-Service
• Hardware

By Technology

• Natural Language Processing
• Context-Aware Computing
• Computer Vision
• Machine Learning

By End User

• Hospitals and Clinics
• Mental Health Centers
• Research Institutions
• Others

COMPANIES PROFILED

• Aiberry, AiCure, Big Health, Cognoa, Inc., Ellipsis Health, Flow Neuroscience, Headspace Health, Infinit Care Inc., Kintsugi Mindful Wellness, Inc., Limbic, Lyra Health, Inc., meQuilibrium Inc., Meru Health Inc., MindDoc (Schoen Clinic Group), Quartet Health, Inc., SilverCloud Health (Amwell), Spring Health Inc. (Spring Care, Inc.), Syra Health, Woebot Health, Wysa Ltd

TABLE OF CONTENTS

Chapter 1. PREFACE

• 1.1. Market Segmentation & Scope
• 1.2. Market Definition
• 1.3. Information Procurement
  • 1.3.1 Information Analysis
  • 1.3.2 Market Formulation & Data Visualization
  • 1.3.3 Data Validation & Publishing
• 1.4. Research Scope and Assumptions
  • 1.4.1 List of Data Sources

Chapter 2. EXECUTIVE SUMMARY

• 2.1. Market Snapshot
• 2.2. Segmental Outlook
• 2.3. Competitive Outlook

Chapter 3. MARKET VARIABLES, TRENDS, FRAMEWORK

• 3.1. Market Lineage Outlook
• 3.2. Penetration & Growth Prospect Mapping
• 3.3. Value Chain Analysis
• 3.4. Regulatory Framework
  • 3.4.1 Standards & Compliance
  • 3.4.2 Regulatory Impact Analysis
• 3.5. Market Dynamics
  • 3.5.1 Market Drivers
  • 3.5.2 Market Restraints
  • 3.5.3 Market Opportunities
  • 3.5.4 Market Challenges
• 3.6. Porter's Five Forces Analysis
• 3.7. PESTLE Analysis

Chapter 4. GLOBAL ARTIFICIAL INTELLIGENCE IN MENTAL HEALTH MARKET: BY COMPONENT 2022-2034 (USD MN)

• 4.1. Market Analysis, Insights and Forecast Component
• 4.2. Software-as-a-Service Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.3. Hardware Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 5. GLOBAL ARTIFICIAL INTELLIGENCE IN MENTAL HEALTH MARKET: BY TECHNOLOGY 2022-2034 (USD MN)

• 5.1. Market Analysis, Insights and Forecast Technology
• 5.2. Natural Language Processing Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.3. Context-Aware Computing Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.4. Computer Vision Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.5. Machine Learning Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 6. GLOBAL ARTIFICIAL INTELLIGENCE IN MENTAL HEALTH MARKET: BY END USER 2022-2034 (USD MN)

• 6.1. Market Analysis, Insights and Forecast End User
• 6.2. Hospitals and Clinics Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.3. Mental Health Centers Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.4. Research Institutions Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.5. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 7. GLOBAL ARTIFICIAL INTELLIGENCE IN MENTAL HEALTH MARKET: BY REGION 2022-2034 (USD MN)

• 7.1. Regional Outlook
• 7.2. North America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 7.2.1 By Component
  • 7.2.2 By Technology
  • 7.2.3 By End User
  • 7.2.4 United States
  • 7.2.5 Canada
  • 7.2.6 Mexico
• 7.3. Europe Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 7.3.1 By Component
  • 7.3.2 By Technology
  • 7.3.3 By End User
  • 7.3.4 United Kingdom
  • 7.3.5 France
  • 7.3.6 Germany
  • 7.3.7 Italy
  • 7.3.8 Russia
  • 7.3.9 Rest Of Europe
• 7.4. Asia-Pacific Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 7.4.1 By Component
  • 7.4.2 By Technology
  • 7.4.3 By End User
  • 7.4.4 India
  • 7.4.5 Japan
  • 7.4.6 South Korea
  • 7.4.7 Australia
  • 7.4.8 South East Asia
  • 7.4.9 Rest Of Asia Pacific
• 7.5. Latin America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 7.5.1 By Component
  • 7.5.2 By Technology
  • 7.5.3 By End User
  • 7.5.4 Brazil
  • 7.5.5 Argentina
  • 7.5.6 Peru
  • 7.5.7 Chile
  • 7.5.8 Rest of Latin America
• 7.6. Middle East & Africa Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 7.6.1 By Component
  • 7.6.2 By Technology
  • 7.6.3 By End User
  • 7.6.4 Saudi Arabia
  • 7.6.5 UAE
  • 7.6.6 Israel
  • 7.6.7 South Africa
  • 7.6.8 Rest of the Middle East And Africa

Chapter 8. COMPETITIVE LANDSCAPE

• 8.1. Recent Developments
• 8.2. Company Categorization
• 8.3. Supply Chain & Channel Partners (based on availability)
• 8.4. Market Share & Positioning Analysis (based on availability)
• 8.5. Vendor Landscape (based on availability)
• 8.6. Strategy Mapping

Chapter 9. COMPANY PROFILES OF GLOBAL ARTIFICIAL INTELLIGENCE IN MENTAL HEALTH INDUSTRY

• 9.1. Top Companies Market Share Analysis
• 9.2. Company Profiles
  • 9.2.1 Aiberry
  • 9.2.2 AiCure
  • 9.2.3 Big Health
  • 9.2.4 CognoaInc
  • 9.2.5 Ellipsis Health
  • 9.2.6 Flow Neuroscience
  • 9.2.7 Headspace Health
  • 9.2.8 Infinit Care Inc
  • 9.2.9 Kintsugi Mindful WellnessInc
  • 9.2.10 Limbic
  • 9.2.11 Lyra HealthInc
  • 9.2.12 MeQuilibrium Inc
  • 9.2.13 Meru Health Inc
  • 9.2.14 MindDoc (Schoen Clinic Group)
  • 9.2.15 Quartet HealthInc
  • 9.2.16 SilverCloud Health (Amwell)
  • 9.2.17 Spring Health Inc. (Spring Care, Inc.)
  • 9.2.18 Syra Health
  • 9.2.19 Woebot Health
  • 9.2.20 Wysa Ltd