Global Artificial Intelligence in Mental Health Market Growth (Status and Outlook) 2025-2031
Description
According to this study, the global Artificial Intelligence in Mental Health market size will reach US$ 1730 million by 2031.
Artificial Intelligence in Mental Health refers to the application of artificial intelligence technology to the entire process of prevention, screening, diagnosis, treatment, rehabilitation and management of mental health diseases. It analyzes the patient's speech, expression, behavior, physiological data, genetic data, environmental factors and other multi-dimensional information through machine learning, deep learning, natural language processing and other technologies, to assist doctors in the early identification, accurate diagnosis and personalized treatment of mental illness. For example, it uses AI depression assessment system to assess depressive symptoms, provides real-time psychological support through chatbots, and optimizes treatment plans in combination with bio-emotional mental models. At the same time, it uses wearable devices and mobile applications to monitor the patient's status in real time and warn of relapse risks. Its core value lies in making up for the shortage of mental medical resources and improving the efficiency and quality of diagnosis and treatment. However, it should be noted that it cannot completely replace the professional judgment and humanistic care of doctors, and it needs to address challenges such as data privacy, algorithm reliability, and ethical laws.
Analysis of future development trends, driving factors and obstacles of Artificial Intelligence in Mental Health
I. Development Trends
Deepening of multimodal interaction and precision services
Artificial intelligence will integrate multi-dimensional data such as voice, text, facial expressions, and biological signals (such as heart rate and brain waves) to improve the accuracy of emotion recognition and psychological state assessment. For example, predicting depression risk by analyzing changes in voice intonation, or identifying anxiety patterns in combination with eye tracking technology.
Personalized intervention plans will be more in line with user needs, such as customizing chatbot dialogue strategies based on user cultural background and language habits, or using virtual reality (VR) technology to simulate user fear scenarios for desensitization training.
II. Driving Factors
Technological Breakthroughs and Cost Reductions
The maturity of technologies such as natural language processing and computer vision enables AI to interact with users more naturally and improve service accessibility. For example, chatbots can provide emotional support 24 hours a day to alleviate the shortage of psychologists. The development of cloud computing and edge computing has lowered the hardware threshold for AI applications and promoted the penetration of technology into primary medical institutions and communities.
III. Obstacles
Privacy and Security Risks
Mental health data is highly sensitive and may lead to discrimination, stigmatization and other consequences once leaked. Although technical means can reduce risks, users’ concerns about data security may still hinder the acceptance of AI services. Risk of hacker attacks or algorithm abuse: Malicious users may tamper with AI models, spread false information, or induce users to engage in extreme behavior.
LPI (LP Information)' newest research report, the “Artificial Intelligence in Mental Health Industry Forecast” looks at past sales and reviews total world Artificial Intelligence in Mental Health sales in 2024, providing a comprehensive analysis by region and market sector of projected Artificial Intelligence in Mental Health sales for 2025 through 2031. With Artificial Intelligence in Mental Health sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Artificial Intelligence in Mental Health industry.
This Insight Report provides a comprehensive analysis of the global Artificial Intelligence in Mental Health landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on Artificial Intelligence in Mental Health portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Artificial Intelligence in Mental Health market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Artificial Intelligence in Mental Health and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Artificial Intelligence in Mental Health.
This report presents a comprehensive overview, market shares, and growth opportunities of Artificial Intelligence in Mental Health market by product type, application, key players and key regions and countries.
Segmentation by Type:
Software
AI Robot
Others
Segmentation by Application:
Diagnosis and Prediction
Personalized Treatment
Detection and Early Warning
Education and Scientific Research
Others
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Woebot Health
Bark Technologies
BioBeats
Cognoa
Lyra Health
meQuilibrium
Quartet Health
Spring Health
Meru
Wysa Ltd
Xunfei Healthcare
Aminer
Leading AI
Mirrorego
Shuye Intelligence
Heal AI
Xinchen AI
Wonderlab
Deepblue AI
Please note: The report will take approximately 2 business days to prepare and deliver.
Artificial Intelligence in Mental Health refers to the application of artificial intelligence technology to the entire process of prevention, screening, diagnosis, treatment, rehabilitation and management of mental health diseases. It analyzes the patient's speech, expression, behavior, physiological data, genetic data, environmental factors and other multi-dimensional information through machine learning, deep learning, natural language processing and other technologies, to assist doctors in the early identification, accurate diagnosis and personalized treatment of mental illness. For example, it uses AI depression assessment system to assess depressive symptoms, provides real-time psychological support through chatbots, and optimizes treatment plans in combination with bio-emotional mental models. At the same time, it uses wearable devices and mobile applications to monitor the patient's status in real time and warn of relapse risks. Its core value lies in making up for the shortage of mental medical resources and improving the efficiency and quality of diagnosis and treatment. However, it should be noted that it cannot completely replace the professional judgment and humanistic care of doctors, and it needs to address challenges such as data privacy, algorithm reliability, and ethical laws.
Analysis of future development trends, driving factors and obstacles of Artificial Intelligence in Mental Health
I. Development Trends
Deepening of multimodal interaction and precision services
Artificial intelligence will integrate multi-dimensional data such as voice, text, facial expressions, and biological signals (such as heart rate and brain waves) to improve the accuracy of emotion recognition and psychological state assessment. For example, predicting depression risk by analyzing changes in voice intonation, or identifying anxiety patterns in combination with eye tracking technology.
Personalized intervention plans will be more in line with user needs, such as customizing chatbot dialogue strategies based on user cultural background and language habits, or using virtual reality (VR) technology to simulate user fear scenarios for desensitization training.
II. Driving Factors
Technological Breakthroughs and Cost Reductions
The maturity of technologies such as natural language processing and computer vision enables AI to interact with users more naturally and improve service accessibility. For example, chatbots can provide emotional support 24 hours a day to alleviate the shortage of psychologists. The development of cloud computing and edge computing has lowered the hardware threshold for AI applications and promoted the penetration of technology into primary medical institutions and communities.
III. Obstacles
Privacy and Security Risks
Mental health data is highly sensitive and may lead to discrimination, stigmatization and other consequences once leaked. Although technical means can reduce risks, users’ concerns about data security may still hinder the acceptance of AI services. Risk of hacker attacks or algorithm abuse: Malicious users may tamper with AI models, spread false information, or induce users to engage in extreme behavior.
LPI (LP Information)' newest research report, the “Artificial Intelligence in Mental Health Industry Forecast” looks at past sales and reviews total world Artificial Intelligence in Mental Health sales in 2024, providing a comprehensive analysis by region and market sector of projected Artificial Intelligence in Mental Health sales for 2025 through 2031. With Artificial Intelligence in Mental Health sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Artificial Intelligence in Mental Health industry.
This Insight Report provides a comprehensive analysis of the global Artificial Intelligence in Mental Health landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on Artificial Intelligence in Mental Health portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Artificial Intelligence in Mental Health market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Artificial Intelligence in Mental Health and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Artificial Intelligence in Mental Health.
This report presents a comprehensive overview, market shares, and growth opportunities of Artificial Intelligence in Mental Health market by product type, application, key players and key regions and countries.
Segmentation by Type:
Software
AI Robot
Others
Segmentation by Application:
Diagnosis and Prediction
Personalized Treatment
Detection and Early Warning
Education and Scientific Research
Others
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Woebot Health
Bark Technologies
BioBeats
Cognoa
Lyra Health
meQuilibrium
Quartet Health
Spring Health
Meru
Wysa Ltd
Xunfei Healthcare
Aminer
Leading AI
Mirrorego
Shuye Intelligence
Heal AI
Xinchen AI
Wonderlab
Deepblue AI
Please note: The report will take approximately 2 business days to prepare and deliver.
Table of Contents
121 Pages
- *This is a tentative TOC and the final deliverable is subject to change.*
- 1 Scope of the Report
- 2 Executive Summary
- 3 Artificial Intelligence in Mental Health Key Players
- 4 Artificial Intelligence in Mental Health by Regions
- 5 United States
- 6 Europe
- 7 China
- 8 Rest of World
- 9 Market Drivers, Challenges and Trends
- 10 Key Investors in Artificial Intelligence in Mental Health
- 11 Key Players Analysis
- 12 Research Findings and Conclusion
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