Introduction

In today's world, social and economic pressures have placed significant strain on people's way of life, bringing mental health concerns to the forefront, on par with physical health. Coupled with the rapid advancements in artificial intelligence (AI), there has been a growing trend of leveraging AI in commercial applications to support mental well-being. In particular, AI systems are able to learn their users’ behavior and to accurately process large quantities of information without tiring or asking for a day off, and so their use now offers the possibility of tracking an individual’s emotional life and providing highly personalized advice relevant to this. By delivering these services through an app, individuals will thus be provided with easily accessible, 24-hour help with stress, depression or other mental health issues.

The application of AI in mental health care not only reduces the workload of medical professionals but also helps address mental health issues at an early stage, enhancing the standard of care in a rapidly changing digital era. For organizations, investing in AI solutions—both proactive and preventive—to support employees' mental health can create value, boost productivity, enhance psychological safety, and deepen broader employee engagement with the company. This, in turn, enables employees to provide better customer services and positively impacts the organization's long-term image.
 

Mental health in Thailand: A major issue in need of support

Worsening problems with mental health in Thailand can no longer be ignored, and indeed, data from the Ministry of Public Health^1/ shows that in 2023, of the 65 million people in the country, an estimated 10 million individuals had suffered from a mental health problem but only 2.9 million had received treatment for this. Something like two-thirds of those affected by these issues are thus suffering outside the reach of the medical establishment. This is partly because as of 2022, for every 100,000 members of the public, there were only 8.99 mental health professionals working in the national healthcare system. Of these, 1.28 were psychiatrists, 1.57 were clinical psychologists, and 6.14 were psychiatric nurses.^2/ This was lower than the recommendations set by the World Health Organization (WHO), both in terms of the global average of 13 per 100,000 population and the average for upper-middle-income countries of 14.7 per 100,000 population.^3/

In addition to problems with a lack of trained staff, work remains a major source of mental health problems and so working-age individuals are significantly more likely to experience mental health problems than are other age cohorts.^4/ These problems typically begin as stress, but when this is left untreated for an extended period of time, this can worsen and potentially develop into a full-blown mental health condition such as anxiety disorder, insomnia, or depression. This is underlined by a survey carried out by the Department of Mental Health in 2023 that shows that a full 40% of working-age individuals reported experiencing high levels of stress.^5/ This finding then mirrors data from the mental health helpline that shows that in June 2024, more than 70% of working-age callers wanted help with stress, anxiety or general unhappiness related to their work.^6/

These two features of the mental health landscape, that is, growing demand for mental health services especially from working-age individuals and the limited supply of qualified professionals, are adding to the attractiveness of AI-based solutions, and because deploying these will help to increase access to care, this will generate significant positive benefits across society at large.  

Getting to know AI in mental health

What is AI in mental health?

‘AI in mental health’ refers to the use of AI technology to assist with the tracking and assessment of mental health issues and the application of this information to support personalized care and treatment, from the first reporting of symptoms onwards.^7/ AI can thus be used as a kind of ‘virtual therapist’ to provide assistance to those looking for support, and to do so round the clock. These services are built on the following technology stack.  

1. Machine Learning (ML) Machine learning (ML) encompasses a broad suite of technologies that are used to analyze data, often at scale, including in the current context data drawn from clients’ behavior or contained in electronic health records (EHRs). This can be used to support accurate diagnoses of mental health conditions, such as anxiety, depression and schizophrenia,^8/ and then to recommend personalized treatment programs. In addition, by learning from a database of previous survey responses and diagnoses and using this to analyze data from patient questionnaires, these systems can assess the likelihood that a new client or user is affected by a particular condition.^9/ However, collecting data from EHR systems in Thailand must comply with various relevant data regulations and laws. These include article 7 of the 2007 National Health Act which states that personal health data is confidential and cannot be disclosed without the explicit consent of the data owner^10/ as well as the 2019 Personal Data Protection Act (PDPA) stipulates that the collection, storage, and use of personal data require the consent of the data owner.^11/
2. Natural language processing (NLP) technologies allow the computerized analysis of human language. NLP, in particular sentiment analysis, can be used to record spoken or written communications and then to assess its emotional content, in the former case through an analysis of its pitch, tone, and rhythm. Chatbots that make use of NLP systems can therefore be used to communicate with users in a natural, human-like way that allows computerized systems to respond to queries, give advice, and even to generate mental-health care plans that are based on user-supplied data.^12/
3. Computer Vision (CV) Computer vision (CV) systems can be used to record and analyze users’ facial expressions, and to assess an individual’s likely level of happiness or whether they are affected by depression or anxiety. Indeed, even subtle facial expressions can be caught, analyzed, and then used to support a diagnosis. CV can also be used to analyze an individual’s posture and body language through their movements, such as analyzing sleep behavior by observing movements, turning, and even signs of restless sleep.^13/

The market for AI in mental health

Interest in the use of AI to address mental health problems is rising rapidly, and while Polaris Market Research estimates that the global market for AI in mental health had a value of USD 0.92 billion in 2023, this should explode to USD 10.33 billion by 2032, or compound annual growth of 30.8%.^14/ This will thus be one of the most exciting areas of progress in AI. In a similar vein, Grand View Research^15/  has found that the most common mental health condition treated by AI is anxiety, which comprises around a third of the entire market. This is followed in importance by depression (30.2%), insomnia (8.2%), schizophrenia (4.5%), and post-traumatic stress disorder (4.2%).^16/

AI-based mental health treatments

• Anxiety and depression

These are the most commonly reported mental health problems, but individuals affected by these conditions can be helped by AI-enabled chatbots such as Wysa and Youper. These make use of techniques derived from cognitive behavioral therapy (CBT)17/  to help users adjust their thought processes and behaviors and to learn tactics for dealing with negative thoughts. By applying these strategies across a broad range of situations, users are able to adopt a more positive outlook and to overcome the self-damaging beliefs that often trigger depression and anxiety.

• Insomnia

People with insomnia have difficulty sleeping, though this can manifest in different ways, and while some individuals may not be able to get to sleep at all, others may fall asleep normally but then wake in the middle of the night or in the early morning and be unable to get back to sleep.^18/ Two apps that can help with this are Calm and Headspace, which offer guided meditations and relaxation techniques as well as narrated stories, soothing music and the sounds of nature. As their names suggest, these apps claim to help users feel calmer and more relaxed, which should then improve sleep quality.

• Schizophrenia

Although full-blown schizophrenia is a serious condition that needs to be treated by trained professionals, there is still room for apps to assist with the therapeutic process. An example of this is Health Storylines,^19/ which helps users to make a daily record of their condition and any changes in their symptoms. The app also helps individuals track their consumption of medicine, a common problem for people with schizophrenia. The app then collates this information and prepares a health report for their doctor or another health professional to check, thereby making it easier to track how their condition is progressing and to decide whether it is necessary to make any adjustments to their treatment plan.

• Post-traumatic stress disorder (PTSD)

PTSD can be treated using Virtual Reality (VR), in particular through virtual reality exposure therapy (VRET). This allows users to gradually re-experience the event or memory that triggers their PTSD but to do so within a virtual environment and under the guidance of a trained and experienced health professional.^20/ This allows someone with PTSD to practice dealing with the problematic memory or emotion in a controlled environment without being exposed to the risks entailed in having to deal with these situations in reality. This then leads to a gradual reduction in the impact of these past experiences on their life.
 

The opportunities and challenges involved in AI-based treatments

Advantages of using AI to treat mental health conditions

Users are able to access AI services delivered through chatbots at all times of the day and night, regardless of where they may be. Individuals with mental health concerns but who are in areas where they have no immediate access to mental health professionals may therefore still receive a preliminary diagnosis and a suggested treatment plan at times and in locations that are convenient to them. In addition to improving access to mental health care,^21/ using AI also means that an individual’s dependency on direct contact with healthcare professionals will be lessened, thereby reducing pressure on budgets arising from the delivery of what can be costly services. For example, in 2022, Headspace partnered with a leading global corporation to analyze the cost implications of using the Headspace app to help with employee health and welfare, finding that this helped to cut spending related to employees’ mental healthcare by 15%.^22/

Some individuals have great difficulty discussing their mental health in person, even when talking to a therapist or psychiatrist, but because explaining one’s situation to an AI avoids the need to interact with another person, it may be easier for some users to open up and to provide much more detailed diagnostic information. On the other side, using AI may also help to overcome some of the limitations involved in relying on a human expert to deliver a diagnosis. These can include straightforward errors, bias, and mistakes arising from being tired, distracted or otherwise performing sub-optimally.^23/

Deploying AI can help to reduce pressure on healthcare workers. In particular, chatbots can be used to give basic advice to users or to undertake a preliminary assessment and diagnosis, with the results of this then sent to a medical professional for further action if this meets predetermined criteria. This will help experts focus their attention on individuals with more complex or more severe conditions.^24/ A local example of this is the DMIND app, which has been jointly developed by the faculties of medicine and engineering at Chulalongkorn University. This uses an AI system to assess an individual’s emotional state and then to rate this on a points-based scale. If an individual qualifies as ‘depressed’, they will be contacted by a clinical psychologist within 7 days, but if they meet the criteria for being ‘acutely depressed’, they will be contacted within 24 hours.^25/

These AI chatbot-based systems train individuals in techniques taken from CBT, which then help these users to change their behaviors. Integrating these strategies into their services helps the AI to identify early signs of mental health problems and then to intervene to address these before they have a chance to worsen and develop into a more serious condition.^26/
 

Challenges arising from the use of AI in the treatment of mental health issues

While it is clearly the case that using AI to support treatments for mental health problems offers many positives, it is equally clear that the deployment of AI systems will bring with it a new set of challenges.   

AI in mental health requires a large amount of personal data to train models for accurate diagnosis or mental health advice. Therefore, preventing privacy violations, ethical breaches, and data leaks^27/  is crucial for creating systems that are secure against cyberattacks. All data used to develop AI models must be obtained with the consent of the patients. These necessities are mirrored in the regulatory requirements to abide by the 2007 National Health Act and the 2019 Personal Data Protection Act. Given this, it is essential that any companies developing mental health AI systems work tirelessly to maintain the privacy of users and datasets and to adhere strictly to their legal obligations, though if they do this, they will help to build trust and establish in users a belief that their data will be handled sensitively and ethically.

2) Humans need to remain in the loop

Since AI models for mental health rely on the data used for training, any bias in the initial dataset will result in biased diagnoses or advice for patients, ultimately affecting the accuracy of evaluations and treatment recommendations.^29/ Given this, to be certain that AI systems are accurate, they need to be trained on datasets that reflect the diversity of end users with regard to factors including age, race, and culture.

Apps and gadgets targeting the mental health market

• Wysa  

Wysa is an app that provides support for individuals with mental health issues, specifically by helping users adopt techniques taken from CBT that help them to better understand and manage negative thoughts and behaviors. Wysa uses an English text-based chat interface called the ‘pocket penguin’ to interact with users in a friendly and informal way to guide them through their therapeutic journey. Initially, the app makes an assessment of the user’s current mental health, the risk that they are suffering from depression and the extent of their anxiety, and this data is then used by the AI system to better understand the user and their needs. A report by Wysa shows that 31%^30/ of users with depression see an improvement in their condition . Wysa also allows users to access consultations with mental health experts via the chat interface.  

• Youper

Youper is another chat-based app that takes advantage of AI to communicate naturally with users. The app uses CBT principles to help individuals improve their understanding of their emotional life and to better manage troublesome thoughts and feelings. In addition, Youper has been studied by researchers from Stanford University and has been shown to effectively reduce symptoms of anxiety and depression after continuous use for two weeks.^31/

• Headspace

Headspace offers users training in meditation and mindfulness with the aim of reducing anxiety and improving sleep quality.^32/ Thus, in addition to guided meditations, Headspace also helps users learn exercises that can help reduce anxiety or other negative emotion experienced in normal day-to-day life, including stress-reducing breathing exercises, body relaxation techniques, and ways of improving emotional awareness and acceptance. Beyond this, the app also helps users address problems with insomnia through its Sleepcast, Soundscape, and Sleep Music features, which provide access to respectively narrated stories, sounds of nature (e.g., rainfall and running water) and soothing music.

• Friend

Friend is an AI-enabled pendant worn on a necklace. Users can interact with Friend by speaking while pressing a button on the pendant. The device also continuously listens to ambient noise through its built-in microphone. By pressing a button on the Friend, wearers are able to chat with the device, which will send responses to a phone to which it is linked via Bluetooth. However, when it is switched on, the Friend is always activated and listening to what is happening around it and so it is possible for the Friend to initiate conversations with the wearer, rather than being restricted to responding to user-initiated prompts. The Friend can thus help to relieve feelings of loneliness by developing human-like relationships with wearers across a wide range of different situations. Advance orders are now being taken, with deliveries expected to begin in 2025. The device is priced at USD 99, though at present it is only available in the US and Canada .^33/

• Moflin

The Moflin is an AI-powered robotic hamster-like pet that has AI abilities allowing it to learn about its owners and to adapt its behavior to their moods. The robot is programmed to interact closely with its owners and to react positively to being petted and stroked, which it registers through touch and motion sensors distributed across its body. This allows it to closely mimic the actions of a real pet, which is then reinforced by the fact that the Moflin’s development and the extent to which it displays a wide range of emotions and responds to others will be guided by its interactions with its users. This has clearly been designed to function as an emotional support for individuals, and much as real pets do, the Moflin can help to reduce feelings of loneliness or stress, thus making it very suitable for some people struggling with mental health problems. The Moflin has been on sale in Japan since November 2024 priced at JPY 59,400 (approximately USD 398).^34/

AI in mental health and its applications in organizations​

Employee mental health is a critical issue that directly affects workplace productivity,^35/ introducing AI for mental health applications into the work environment can have significant positive impacts across the organization. Some of these are described below.

• Establishing an open organizational culture: Using AI to support mental health services will help staff to feel that they are in a safe and supportive environment and within this, individuals dealing with mental health problems can talk about these issues without shame or stigma. In addition, the accuracy of AI-driven data analysis will help employees understand the factors that influence overall levels of staff anxiety and mental well-being, and in turn, this will allow executives and staff to work together to create a workplace where individuals are supportive and understanding of one another.

• Driving enterprise-level development through innovation: Using AI to help staff deal with mental health challenges will allow the enterprise to present a modern, progressive image and to position itself at the forefront of the digital revolution. This will also underscore the ability of the enterprise to respond to the challenges presented by modern lifestyles and to make it an appealing workplace, both for those already there and for those who are not yet its employees.

• Attracting skilled professionals: Companies that offer progressive policies for supporting staff mental health that are strongly differentiated from those offered by other employers (e.g., that explicitly cover the healthcare cost of treatment for mental health issues),^36/ that promote physical exercise (e.g., by paying for gym membership),^37/ and that offer staff access to apps that help with mindfulness and meditation38/ are likely to attract more skilled employees, especially from younger staff who are more concerned with issues connected to mental health and wellbeing. At the same time, employee morale will also be higher and staff will feel more engaged with the enterprise, thus reducing staff wastage.

• Improving brand or corporate image: Companies that prioritize psychological safety^39/   in the workplace, for example, by supporting employees' mental health through tools like AI-enabled programs, can improve image in the eyes of customers, investors, and the wider society. This should then help to sustain a positive public image for the corporation over the long term.

Using AI to support employee mental health is an investment in human resources, the most crucial asset of any organization, alongside investments in innovation. This approach not only helps employees achieve better mental well-being and foster a positive attitude toward their work but also forms a strong foundation for organizational development in the digital era. However, improving employee mental health cannot rely solely on AI tools. It must be integrated with the organization's core culture, leadership vision, and each company’s unique definition of work-life balance.

Krungsri Research’s view

Given how difficult it is to avoid work-related stress, companies need to be engaged in staff welfare and mental health initiatives that target these issues at their earliest stages. This will particularly involve the use of AI-enabled mental health applications since these can help to head off issues related to stress before these develop into burnout or other mental health problems. Corporations, including banks, should therefore consider engaging in the following initiatives.

• Proactive Employee Support

To support staff wellbeing, companies can institute employee assistance programs.^40/  This can begin with the use of AI systems to assess employees’ mental health and to identify any current or potential problems in this area. The results of this analysis can then be used to design personalized treatment programs and to support staff seeking in-person or online consultations with healthcare professionals. In addition to promoting better mental health and deepening staff engagement with the company, programs such as this will help to tackle absenteeism, presenteeism, and turnover. As an example of this, a study by a major US company employing more than 50,000 staff found that setting up an employee assistance program generated savings of USD 29 million annually, or an average of USD 580 per staff member.^41/ Additionally, companies may implement AI in mental health through their in-house applications that employees use on a daily basis. This can then generate proactive nudges to encourage users to undertake some kind of activity that will be beneficial to their mental health or to shift their behavior towards something more positive, but without exerting explicit pressure to do so. This could include recommending that they take a break, warning that they are working too much, or suggesting leisure activities such as walking or easy stretching exercises that can help promote relaxation and de-stressing.

• Preventive Employee Support

Because stress is often at the root of poor mental health, introducing AI-enabled tech solutions into work environments that typically generate high levels of stress can help to reduce the rate at which these problems occur. In particular, using AI to support direct customer-facing service roles can yield considerable benefits since individuals in these positions are often under significant pressure. In the banking environment, AI has the potential to alleviate pressure on staff working in call centers, where the introduction of chatbots and virtual assistants can be used to deliver round-the-clock customer services. In addition, banks should consider developing generative AI^42/-enabled  databases to help branch officers more accurately identify financial products and services that are a match for individual customer needs. Home loan officers are also exposed to work-related stress, especially in an economic climate that remains somewhat unfavorable for the real estate market. However, it is now possible to use AI to develop home loan approval systems that allow for appraisals to be made without an on-site visit^43/  and this would help to ease the workload for individuals responsible for this. Beyond site inspections, AI can also help with the processing of paperwork, further addressing the sources of long-term stress.

Any decline in staff wellbeing will likely have direct impacts on their performance at work and this will then feed through into a decline in the company’s overall operations, but the reverse of this is that providing improved support for staff welfare, reducing incidences of work-related stress and strengthening overall levels of employee morale will lower costs, improve performance and increase the quality and care of customer service. In this case, customers will therefore experience greater levels of satisfaction and as trust in the company deepens, their willingness to engage with the company will likewise develop, further building the foundations needed to support long-term sustainable growth.

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