Every field is adapting usage of AI to enhance the system. Mental health care is not an exception. In this post, I’ll explore how AI is being used in mental healthcare, using real-world examples and research studies to examine both its current applications and future possibilities.

Mental Health Concerns in Singapore

The following are some of the key mental health concerns identified in Singaporean statistics. All information is drawn from reports published in 2024 to 2025 by national and healthcare sources, including the Ministry of Health (MOH), The Straits Times, and NUHS.

• One in three young people aged 15 to 35 in Singapore reported experiencing severe or extremely severe symptoms of depression, anxiety, or stress. [link]
• Key contributing factors include academic pressure, excessive social media use, cyberbullying, and body-image concerns. [link]
• Children aged 10 to 14 in Singapore also experience mental health disorders.[link]
• Singapore’s rapidly ageing population faces challenges such as late-life depression, often linked to declining physical health and social isolation. [link]

These findings demonstrate the growing need for accessible and effective mental health support in Singapore. Before exploring the role of AI, let us first look at how government agencies and healthcare institutions are responding to these concerns.

How Singapore Is Addressing Mental Health Concerns

The above reports show that mental health is a significant concern in Singapore. To address these challenges, government agencies and healthcare institutions have introduced various initiatives to improve access to mental health support, encourage early intervention, and reduce the pressure on healthcare professionals.

These are some of the existing approaches:

• National mental health programmes and public awareness campaigns.
• Mental health support in schools and workplaces.
• Helplines, counselling services, and community-based care.
• Early screening and intervention programmes.
• Digital mental health platforms and telehealth services

How is AI integrated into the approaches?

AI can contribute to several of these efforts. In particular, it is being explored in two areas: digital mental health support and early screening and intervention.

Digital mental health platforms and telehealth services

Since the emergence of AI chatbots, patients with mental health issues some times use online chatbots to get help in a series of question and answer session. However, using Generative AI chatbots is not ideal in serious cases because of the lack of empathy and sympathy to the specific case. These chatbots cannot be used in serious mental health cases as they might give misinformation, inappropriate responses and might cause harm.

However, some patients prefer the anonymity offered by chatbots. With this in mind, the government has introduced resources tailored to local needs that provide similar anonymous support while guiding users towards appropriate professional referrals.

Early screening and intervention programmes

To detect early signs of deteriorating mental health, several AI-powered screening and detection tools are being introduced.

Voice and speech biomarkers can help identify early signs of subsyndromal depression in older adults. These tools analyse features of a patient’s voice recordings, such as pitch, rhythm, and tension in the vocal cord muscles.

Tablet-based games combined with machine-learning algorithms are also used to screen for mild cognitive impairment with a high degree of accuracy. Hospital-backed applications such as Pensieve assess shape-drawing and clock-drawing tasks to identify possible early signs of pre-dementia.

Project HOPES is a government-supported research initiative exploring whether data from smartphones and wearable devices can help identify changes in a person’s mental health.

Benefits of AI in Mental Healthcare

AI has the potential to make mental health support more accessible. Digital platforms can allow people to seek initial guidance privately, which may be helpful for those who feel uncomfortable discussing their concerns in person. These tools may also help people understand when they should seek professional support.

AI can support earlier intervention by identifying changes in speech, sleep, activity, mood, or behaviour. When concerning patterns are detected early, healthcare professionals may have an opportunity to assess the individual before their condition becomes more severe.

Another potential benefit is continuous monitoring. A person’s mental state can change between appointments, and clinicians cannot observe patients at all times. With appropriate consent, data from smartphones and wearable devices may help track meaningful changes and alert healthcare professionals when further assessment is needed.

AI can also support mental health professionals by analysing large amounts of information, assisting with screening, and identifying patterns that might otherwise be difficult to notice. This may reduce the time spent on repetitive tasks and allow professionals to focus more attention on diagnosis, treatment, and direct patient care.

Limitations and Ethical Concerns

Despite its potential, using AI in mental healthcare comes with serious limitations. Mental health data is highly sensitive and may include personal conversations, behavioural patterns, voice recordings, and information collected from smartphones or wearable devices. Patients need to understand what is being collected, how it will be used, and who will have access to it.

AI predictions are not always accurate. A system may fail to identify someone who needs help or incorrectly classify ordinary behaviour as a warning sign. For this reason, an AI-generated result should not be treated as a confirmed diagnosis.

Bias is another concern. If an AI system is trained using data that does not adequately represent different ages, cultures, languages, or social backgrounds, its predictions may be less accurate for certain groups. This is particularly important in a multicultural society such as Singapore.

AI systems also lack genuine empathy and a complete understanding of a person’s circumstances. A chatbot may recognize words associated with distress, but it cannot fully understand emotions, relationships, cultural context, or non-verbal signals in the way a trained professional can.

Can AI replace Mental Health Professionals?

Due to its limitations and ethical concerns, AI cannot replace mental health professionals. However, it can support professionals and improve the overall experience of receiving mental healthcare.

Since mental health conditions are complex and often influenced by a combination of personal, medical, cultural, and social factors, AI is most valuable when it supports professionals rather than replaces them. Important decisions about diagnosis, treatment, medication, and crisis intervention should remain under the supervision of qualified healthcare professionals.

Conclusion

For now, AI should be viewed as a supporting tool rather than a replacement for mental health professionals. Its greatest value may lie in helping people receive the right support earlier while allowing healthcare professionals to make more informed decisions.