How AI could help treat mental health
From supporting therapists to delivering psychological interventions, AI is beginning to reshape mental healthcare. But how might these tools work in practice, and what safeguards are needed to ensure they benefit people with mental health conditions?
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Qi Yang/Getty Images
10-minute read
10-minute read
Every new day brings multiple headlines about AI, its rapid development and the challenges of regulating it effectively.
This is all part of a wider revolution where digital tools - whether AI-based or not - are being used to tackle a variety of mental health problems, from reducing the distress of people who hear voices, to using Tetris to manage intrusive flashbacks.
The term AI covers several ideas:
- AI itself refers to any computer system designed to perform tasks that normally require human intelligence
- Generative AI is a kind of AI used to generate text, images, or other content
- Large Language Models (LLMs) like OpenAI are designed to process and generate text
- AI Chatbots like ChatGPT are the user-facing platforms built on top of LLMs (though not all chatbots are necessarily AI-powered)
LLMs that are purpose-built for mental health have real potential in the field. Assessment, diagnosis and psychological treatments for mental health problems often rely heavily on language, which is something these models process very effectively.
This opens up a range of possibilities for supporting people who experience mental health problems and their clinicians, and a variety of AI-based tools have already been developed for this purpose. However, as these tools become more and more prevalent, as with any new mental health innovation, we need to examine their potential for causing harm and identify ways to make sure they don’t.
Millions of people around the world report using AI chatbots powered by LLMs to help with their mental health, though in most cases these tools have not been designed for this purpose. Many say they make a positive difference in their lives; however, there is also a risk that they could be causing harm or perpetuating misinformation.
How could AI help with mental health?
Mental health problems affect one in two of us and they’re projected to be the world’s biggest health burden by 2030, costing the global economy $6 trillion each year.
At the same time, healthcare systems and the people who work in them are under considerable and worsening strain, making it difficult for the growing number of people who need care to access it.
There are several areas where AI has the potential to support people experiencing mental health problems and lessen the burden on healthcare professionals too. These include:
- automating routine tasks for therapists such as note-taking, creating reports from data or providing reminders or prompts between therapy sessions
- specialised, evidence-based mental health chatbots that provide accessible, in-the-moment support and therapy to those who need it, including helping them to learn and practise new skills
- training for new therapists, professionals or even volunteers and laypeople who regularly encounter or support people facing mental health problems
- tools to support therapists with reviewing patient data and decision making, integrating varied evidence, displaying it in user-friendly ways and mitigating issues like human error and biases
- fully-automated end-to-end services, where an AI model drives assessment and triage through to treatment delivery and therapeutic decisions
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Okay, so… would you use an AI therapist?
Artificial intelligence and therapy actually goes way back to the 1960s. Meet ELIZA, the world’s first ever AI chatbot. Written with just 420 lines of code, it was designed by this guy to mimic the language of a psychotherapist. Sixty years later, chatbots have come a long, long way. Now they can edit passive aggressive emails to sound more friendly, plan holidays in seconds, and DJ your party on command, as well as acting as your 24/7 therapist.
But let’s be clear. AI therapy is just one of the many stages in mental health’s digital revolution. So much has already happened. There are algorithms that analyse speech to spot early signs of psychosis. Apps that use a simple game of Tetris to help your brain reprocess a traumatic memory. We’ve even got digital avatars that help patients process the voices they hear.
Today, the brains behind AI are promising less admin for therapists, improved training, and perhaps most promisingly, easier access to mental health care. Sounds impressive, right? Well, when it comes to AI and therapy, there’s a lot of different views out there.
So most therapy is a conversation. And conversation is something AI is getting pretty good at. The more powerful models are trained on tonnes of existing written material, identifying common ways each word is used, using that data to piece together a reply to your message. But not every mental health chatbot works the same. One might scan for super‑specific words, like a symptom you typed out, to trigger a reply. One might be slightly more rigid, giving you a list of messages to pick from, each with a prewritten response.
When used for therapy, some people have mentioned how they like the warmth, companionship, and the advice of the chatbot. One described their conversation as a safe space. This study found that an AI model trained on medical data has the potential to help people reframe their negative thoughts. Another concluded that chatbots are just as effective as human therapists for those with depression, anxiety, and eating disorders. However, not everyone has experiences like this. Some research found that others are more frustrated, saying their conversations feel empty, generic, and not knowledgeable enough.
Those with lived experience of mental health conditions have already questioned whether replacing a human therapist with a chatbot could increase isolation, which is exactly what one study by researchers at MIT and OpenAI found. To add to that, most AI chatbots are trained on English language data, often from Western contexts. This raises questions about how well they serve people from different cultures, or those who don’t speak English as a first language.
If training data has a narrow cultural view, AI might ignore important nuances and contexts in your messages, or reinforce harmful stereotypes around race, gender, and sexuality, which could widen existing inequalities. And of course, it’s not just chatbots. Your human therapist can hold these biases too. Either way, whether it’s AI or face to face, those developing the therapy must always work closely with the communities they want to help. They also need to collaborate with ethics experts to make sure the training is inclusive and the support is safe.
If we do this properly, AI could be part of the solution to offering a more effective, consistent approach to mental health care, like one chatbot currently used by the UK’s National Health Service. So far, it’s already making a difference, with faster referral times and nearly every user finding the chatbot helpful. Joyce is actually working on something similar, focusing on speech recognition, powering hospital call centres with AI so more patients can get the care they need.
Although, yes, AI might be capable of speeding up assessments, staff training, note‑taking, or even the waitlist for human therapy, a lot of people have concerns about how all this data is being used and protected. So, who’s regulating the chatbot therapists? And what policies do we need to protect everyone? Or if things really do go wrong while someone is under the care of AI, what happens to them?
Clearly, the role of artificial intelligence in mental health poses lots of questions. We should approach it with caution. But at the same time, there’s this massive potential to expand healthcare access for those who need it most. To make sure that potential is realised in the right way, breakthroughs in technology need to be paired with the right regulation, involving those with lived experience at every stage.
So, one more time… would you use an AI therapist?
How can we use AI for mental health safely and effectively?
When it comes to generative AI, the risks of using LLMs that are specifically designed or adapted for mental health support are likely to be lower than those of using standard publicly available AI chatbots. Polling commissioned by Mental Health UK has found that more than one in three UK adults relies on general-purpose AI chatbots like ChatGPT for mental health support. Two-thirds of respondents said they found this beneficial, citing ease of access, long waiting lists for mental health support and discomfort discussing their mental health with friends and family. However, one in ten said it made them feel more anxious or depressed.
AI-based treatments will be most effective if they are designed specifically for mental health, incorporating the relevant evidence and expertise. However, some in the mental health community still have reservations about using AI even where it has been specifically designed or adapted for use in mental health, arguing that it is at best inferior to human-based treatments, and at worst harmful to people who use it. They share a number of concerns:
- It isn’t yet known whether AI-based tools will be as effective as human-to-human treatment. There is a risk of exacerbating health inequalities in access to high-quality care, with high-income populations treated by therapists and lower-income populations having only access to AI chatbots.
- All datasets are liable to reflect human biases, and LLMs trained from skewed or biased data could reproduce and amplify those biases.
- There is not yet sufficient regulation around the development and use of LLMs, and a lack of transparency and accountability when it comes to privacy, data protection and safety.
- LLMs can have sycophantic tendencies, which can reinforce delusional, harmful or suicidal beliefs.
These are issues worth considering, and with AI already playing a role in healthcare, we need more work to make sure it is deployed safely, effectively and accountably.
Wellcome is actively supporting this, for instance, by funding PATH (Program for Appropriate Technology in Health) to design Africa’s first regulatory sandbox - a virtual space where new tech can be tested - for AI-enabled mental health tools. This will help guide new AI products and develop regulatory pathways while creating new research that can be shared across the continent.
How is AI being deployed in mental healthcare globally?
Tools for AI therapy could prove especially useful in parts of the world where limited resources, stigma or language barriers make local brick-and-mortar mental healthcare particularly difficult to access.
Nearly 150 million people in Africa are affected by mental health problems, but there is a severe shortage of workers trained to deal with them.
Butabika hospital in Kampala, Uganda, has been developing an AI-based chatbot to offer therapy and advice in several local languages, including Swahili and Luganda, and identify when patients might need to be escalated to more specialised care.
Professor Joyce Nakatumba-Nabende, one of the project’s developers and Scientific Head of the Makerere AI Lab at Makerere University, told the Guardian Newspaper:
“When you automate, it’s faster. You can easily provide more services to people, and you can get a result faster than if you were to train someone to do a medicine degree and then specialise in psychiatry and then do the internship and the training.”
Uganda is far from the only place where generative AI tools are already being deployed to support mental healthcare. In the UK, some NHS sites are using an AI-powered clinical decision support tool to improve access while reducing the time it takes clinicians to assess and triage new referrals.
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How is Wellcome supporting research on AI and mental health?
At Wellcome, we are working towards a world where no one is held back by mental health problems, and we want to understand the role that AI has to play in achieving this.
This is why we’re funding fundamental research on generative AI and mental health, with the goal of better measuring and treating conditions such as anxiety, depression and psychosis.
Our first programme, which focused specifically on Gen AI and mental health, launched in 2025. Shortlisted applicants participated in a four-month accelerator delivered by Neuromatch, and could then apply to our full funding call. Successful teams have been awarded up to £3 million each for up to two years, with access to resources and support from experts at Google DeepMind and Gooey AI. The 14 successful teams are now delivering their projects, focused on enhancing mental healthcare using generative AI.
Led by Prof Vikram Patel, Harvard Medical School is developing and testing an AI‑enabled supervision tool to strengthen psychological treatment quality delivered by non‑specialist counsellors in India.
Prof Lauren K White, leading this project at the Children’s Hospital of Philadelphia, is using generative AI to detect how anxiety signals move between parents and children by analysing multimodal behavioural and emotional cues.
New York University, led by Prof Joao Sedoc, is creating controllable, AI‑powered digital patient simulations to train clinicians using realistic psychiatric presentations.
Kids Help Phone, led by Dr Lydia Sequira, is building a generative‑AI conversational simulator to train frontline workers and volunteers to better support youth with anxiety and depression.
Led by Dr Isabelle Scott, University of Melbourne is developing SensAI, a generative‑AI collaborator that supports personalised, collaborative care for young people with anxiety and depression.
Baylor College of Medicine, in collaboration with DeliberateAI, is combining passive sensing with voice‑based generative AI check‑ins to generate more accurate, real‑time measurements of depressive symptoms. This project is led by Prof Eric Alan Storch.
Led by Dr Antonio Fernandez Pardinas, Cardiff University is designing an LLM‑based system, informed by lived experience, to produce proxy measurements of psychotic symptoms using multimodal data.
The University of Toronto, led by Prof Syed Ishtiaque, is creating culturally aligned generative‑AI tools to support para‑counsellors providing mental health care in Bangladesh.
Led by Dr Dominic Oliver, the University of Oxford is developing a voice‑based generative‑AI interview system to identify people at high risk for psychosis and produce tailored clinical reports.
The Slum and Rural Health Initiative is building and validating a culturally grounded generative‑AI platform to enhance depression and anxiety screening for major language groups in Nigeria. This project is led by Dr Isaac Olufadewa.
Led by Prof Lekhansh Shukla, the National Institute of Mental Health and Neuro Science is developing a multilingual AI‑assisted pipeline for accurate depression diagnosis and severity scoring across diverse clinical populations.
The African Population and Health Research Centre is creating a bilingual generative‑AI model for culturally adapted screening of depression, anxiety and psychosis in Kenya and Tanzania. This will be led by Dr Tatenda Duncan Kavu.
Freedom from Torture, led by Dr Jacqui Gratton, is developing a generative AI therapeutic companion for torture survivors with PTSD, providing grounding support to clients, generating clinical reports and adapting strategies based on therapist guidance.
Led by Dr Christine Wasanga, the Shamiri Institute is developing shamiriAI, an AI tool that processes session audio, using multilingual Automatic Speech Recognition (ASR) and prosodic analysis to generate structured feedback for supervisors.
Wellcome is also funding research into various digital interventions that have an AI component. One example, AVATAR therapy, aims to reduce the distress that people who hear voices often experience. Patients create a computerised visual and auditory simulation of the voice they hear, then practice dialogues with it, standing up to and challenging the voice to regain a sense of personal power and control. Having already supported the development and testing of AVATAR therapy, Wellcome have now funded the AVATAR team to explore whether these dialogues could be safely powered by AI, overseen by a clinician.
We are at the start of a revolution in mental health treatment. By supporting research that engages with lived experience experts alongside the complex ethical questions surrounding this new technology, we hope to find new ways of providing safe, effective mental health support to those who need it.
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