9 key benefits of artificial intelligence in mental health care

Mental illness affects about 15.5% of the world’s population, and this number is growing. Though many need treatment, over 50% of mental illnesses remain untreated. One in five U.S. adults suffers from some form of mental illness. Every 40 seconds, a person dies from suicide, and more than 20 others have tried to end their lives. The consequences of this extend beyond our families and cultures, as mental health also has a tremendous economic impact on the cost of treatment and loss of productivity.

A critical lack of treatment exacerbates this crisis. Indeed, nearly 40% of Americans live without a mental health professional; 60% of U.S. counties have no psychiatrists. Those who access mental health professionals often forego treatment because they can’t afford it. Depressed individuals visit primary care physicians on average five times a year, while others seek help in costlier emergency rooms. Mental health spending exceeds $201 billion a year, making it the most expensive part of our healthcare system after heart-related conditions.

Examples of Current Mental Health Uses of AI:

Researchers are testing various ways of using artificial intelligence to screen, diagnose, and treat psychological diseases. WWBP researchers analyzed social media using an AI algorithm to identify indicators for predicting depression. It turns out depressed individuals express themselves differently on social media compared to those dealing with other chronic conditions. After analyzing half a million Facebook posts, the team’s results were published in the National Academy of Sciences journal “Proceedings” journal. They found that language markers could predict depression up to three months before a formal diagnosis. Other researchers use technology to explore how facial expressions, words, and language may indicate a risk of suicide.

Several companies, besides researchers, use artificial intelligence to help tackle mental health issues. Quartet Platform identifies potential mental conditions and can refer patients to a cognitive behavioral therapy provider or computerized program. Ginger offers a chat application that employers use to advise staff directly. Its algorithms analyze used words, drawing on training from more than 2 billion behavioral data, 45 million chat messages, and 2 million clinical evaluations. The CompanionMX system has an app that allows patients to receive therapy for depression, bipolar disorders, and other conditions, creating audio logs to discuss their sensations. An AI system analyzes the recordings, seeking proactive monitoring of behavioral changes. Bark, a parental control phone tracker, monitors messages on a child’s phone and social media platforms to identify signs of cyberbullying, depression, suicidal thinking, and inappropriate content.

Key Benefits Of Artificial Intelligence In Mental Health

Here are the key benefits of using AI to solve the mental health crisis.

1. Early Detection

Early detection of mental health problems is crucial for effective treatment. AI has shown promise in detecting markers indicative of early-stage mental health issues, similar to how it can detect markers for early-stage cancer. Traditional mental healthcare relies heavily on observing and reporting changes by individuals and professionals. However, as shown in two recent case studies, AI can analyze data and identify relevant symptoms, acting as a mechanism for early detection.

2. Supporting Mental Health Practitioners

AI can assist mental health professionals in a similar way that it aids professionals in many industries. Algorithms can analyze data significantly faster than humans, suggesting potential treatments, tracking patient progress, and sending alerts. AI would typically work in collaboration with a human clinician.

3. Easy Accessibility

In 2014, around 45% of the world’s population lived in a country with fewer than one psychiatrist per 100,000 people. Access to care is a luxury many cannot afford or have limited access to. AI has the potential to play a significant role in not only personalized treatments but also in improving accessibility to mental healthcare. Ginger.io exemplifies this by providing an online platform that combines AI and machine learning with a network of established clinicians. Ginger.io tailors its approach to user needs and offers access to various treatment options.

4. Reduced Stigma

While less prevalent than before, the stigma surrounding mental health persists. Some people fear judgment from friends or professionals when seeking help. AI chatbots can address this issue by providing a safe space for people to talk about their problems anytime. Some chatbots are trained on mock counselor transcripts, allowing them to handle sensitive issues like suicide.

5. Cost-Effectiveness

Mental illness not only reduces quality of life but also increases healthcare costs. Around $201 billion is spent annually on mental health, and this figure is expected to rise due to population aging and the prevalence of conditions like dementia. Due to high treatment costs, many people with mental health problems don’t receive timely professional support. AI-powered tools could offer a more cost-effective solution.

6. Personalized Treatment Plans

Traditionally, therapists develop treatment plans based on experience and expertise. However, AI can analyze vast data, including a patient’s medical history, symptoms, and responses to past interventions. This allows AI to identify patterns and suggest treatment options with a higher likelihood of success for the individual. This data-driven approach can lead to more targeted and effective treatment, reducing the time patients experience improvement and improving their overall satisfaction with the therapeutic process.

7. Monitoring Mental Health

Mental health conditions can fluctuate over time, and early detection of relapse is crucial for preventing episodes from worsening. AI-powered tools can continuously monitor a person’s mental health by analyzing speech patterns in phone conversations or tracking social media activity. AI can prompt interventions before symptoms become severe by identifying subtle changes that might indicate a relapse. This proactive approach can significantly improve a person’s long-term well-being.

8. Providing 24/7 Support

Factors like geography, finances, or scheduling conflicts can limit access to mental health professionals. AI chatbots can bridge this gap by offering support and companionship anytime, day or night. These chatbots can be programmed to offer basic coping mechanisms, answer questions about mental health conditions, or simply provide a non-judgmental space to vent. This readily available support system can be particularly valuable for people in crises or struggling to manage symptoms between therapy sessions.

9. Improved Self-management

People with mental health conditions often benefit from actively participating in their treatment. AI-based applications can empower individuals by providing educational resources about their specific conditions. These applications can also guide users in developing coping mechanisms tailored to their needs and track their progress over time. This fosters self-management skills, allowing individuals to take greater control of their mental health and enhancing their overall sense of well-being.

Current Landscape of AI in Mental Health Care

AI technology has been widely adopted in mental health care for different purposes, including diagnosing mental health disorders, diagnosis, treatment, and therapy. AI technology is used to predict mental health disorders by analyzing patients’ online activity, social media, and smartphone usage patterns. These tools use machine learning algorithms to identify patterns and warning signs of mental health disorders. Such information can be used to develop targeted intervention strategies to prevent the onset of mental health disorders. AI technology can assist in diagnosing mental health disorders by analyzing speech, facial expressions, and behavior patterns. Such tools use natural language processing, machine learning, and computer vision to diagnose accurately and efficiently. In addition, AI-based chatbots are becoming increasingly popular as a mode of psychotherapy. These chatbots offer 24/7 support to patients, providing self-help resources, cognitive-behavioral therapy, and emotional support. The following are available artificial tools for healthcare and mental health:

  • Chatbots: Chatbots are computer programs that simulate conversations with users. They can be used in mental health to provide support, counseling, and guidance to patients. Some examples of mental health chatbots include Woebot, Wysa, and Youper.
  • Virtual reality therapy: Virtual reality therapy uses computer-generated environments to simulate real-world situations that trigger a patient’s anxiety or phobia. By gradually exposing patients to these environments, virtual reality therapy can help patients overcome their fears. Some examples of virtual reality therapy tools include Limbix, Psious, and Virtually Better.
  • Wearable sensors: Wearable sensors can monitor a patient’s physiological and behavioral responses to stimuli such as stress or anxiety. This information can be used to provide personalized treatment recommendations. Examples of wearable sensors include Fitbit, Apple Watch, and Embrace.
  • Machine learning-based diagnosis: Machine learning algorithms can analyze patient data, such as medical records, genetic information, and imaging data, to provide accurate diagnoses of various medical and mental health conditions. Examples of machine learning-based diagnosis tools include IBM Watson Health and Ayasdi.
  • Natural language processing (NLP) for clinical documentation: NLP tools can extract relevant information from clinical documentation, such as patient notes and medical records. This information can improve clinical decision-making and provide more personalized treatment recommendations. Examples of NLP tools include Clinithink and Linguamatics.


Integrating artificial intelligence (AI) into mental health care represents a revolutionary advancement. By leveraging AI technologies such as machine learning, natural language processing, and wearable sensors, healthcare providers can enhance early detection, diagnosis, and treatment of mental health disorders. Chatbots offer accessible and personalized support to individuals, reducing stigma and overcoming barriers to traditional therapy. Wearable devices provide continuous monitoring, enabling proactive interventions based on real-time data. Moreover, AI-driven predictive analytics facilitate targeted interventions, improving patient outcomes and reducing healthcare system burdens.