There is a quiet revolution taking place in therapists offices and psychiatric clinics all over the world. The revolution is growing every day but most patients wont even realize that AI has entered the room. What comes to mind when someone says the words Artificial Intelligence (AI)? I get images of chatbots, self-driving cars and all sorts of cool science fiction concepts but the reality is that this technology is growing every day and is slowly but powerfully changing the way we receive mental health care and how it can impact our lives. Take a glimpse into 2026 mental health with this AI feature.
There’s no doubt that first point of AI impact is documentation. I know that psychiatrists and therapists have to spend a lot of time writing notes and filling out insurance forms and other digital record keeping. They report that they spend as much time documenting a patient’s history as actually treating the patient. And so there’s now a digital scribe. Clinical recording and transcription tools, such as Amwell and Doctible, record and transcribe patients during sessions with their consent. These tools can also produce clinical notes in real time using automated transcription tools, such as Temi, and allow psychiatrists to have more human interaction and eye contact with patients. The clinical summaries are then reviewed, approved, and merged with other clinical data to create a rich summary of session highlights for both the patient and provider to reflect on.
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While the focus in mental health AI has been on documentation, there is far more potential for transformative change by developing ‘digital biomarkers’. Documentation of patient history and progress has long been a cornerstone of psychiatry, however it has traditionally relied on patient self report. Human memory is fallible, and people often do not realise they are entering into a mental health episode until it is in full swing. However, modern AI systems are able to monitor a wide array of passive signals that a person emits as they go about their life.
Even the way I type out my thoughts and feelings can be a giveaway to what is going on with me. When I’m entering into a depressive episode, my typing slows down, and I take longer to type out a response to messages. My replies are often brief and to the point. In the midst of a manic episode, I type faster, more erratically and haphazardly, slinging words out in a mad daze. Researchers using AI have found that the patterns in the way people talk can be analysed without them realising it. But it may also be possible to pick up on changes in voice – measured in factors such as pitch, speech rate and pause length – that signal that a person is coming down with a illness up to several days before they fall ill.
Wearable tech could soon be able to detect mental health decline by monitoring users for changes in sleep and physical activity, according to researchers. A new system uses AI to scan a whole host of signals coming from a user’s heart rate variability, as well as data about whether they have left home in recent days, taken less sleep than usual or are engaging in less exercise than normal.
It could even use GPS to track whether the user has left home at all in the past few days.
Real-time data has real value in real world use. A busy psychiatrist with a heavy workload and a large patient load can only occasionally glance at the biomarkers. But with digital biomarkers arriving in real time, that busy doctor can see that the patient is in trouble three weeks earlier. He or she can call the patient, or text them during an appointment, or write in the patient portal to have the message sent to the patient before the next appointment. And this can prevent great suffering, and even save lives by preventing hospitalizations for psychoactive medications.
Can AI be used to increase access to mental health care? In many parts of the world there is a lack of trained mental health professionals available to provide the care that is needed, with people having to wait months for an appointment. AI powered mental health tools are not a replacement for a trained therapist, but they can be used to support clients in between sessions. Many apps allow you to track your mood and receive feedback on your entries. Others offer guided relaxation, and modules based around cognitive-behavioral therapy (CBT). They are not a substitute for a proper, living funeral director but they can provide support to individuals who would otherwise receive no funeral service at all.
This whole area is replete with ethics issues because this data can reveal so much about how individuals live their lives and even their personal habits before sleep (e.g., do they read a book or watch TV?) and awake (e.g., do they play video games?). Many people will find this sort of information analysis to be very disturbing. Therefore, it is up to the companies and clinicians using these tools to be extremely transparent about how and what information is collected, stored, accessed and retained. Individuals should have the right to know this information and to opt out if they choose to do so without losing access to medical care.
Note: AI will continue to grow in the use and help for psychological conditions and the technology continues to get better and better.
One problem with relying on AI is that it can increase the chances of false alarms or incorrect diagnosis. Even with the most sophisticated AI, errors can occur if the data it was trained on was flawed. For instance, an AI might flag for an emergency psychiatric assessment of a student who types slowly and has been at home for a week because she is bereaved, rather than suffering from clinical depression. We must use digital data as a supplementary patient tool, not a replacement for our clinical judgment and expertise.
In the following chapters we explore how technology can enhance clinical work using the latest tools such as AI, machine learning and apps. None of the ideas in this book were to suggest that technology is here to replace the most crucial element of clinical work: the therapeutic relationship. In fact, technology can enhance this most important aspect of clinical work by allowing clinicians to be more present in their work. By automating paper work, early intervention of danger through machine learning algorithms, and round the clock support through apps, technology can enhance, not replace, the most important aspect of clinical work: human connection. Technology cannot and should not replace human connection, but it can amplify and extend it. Now the right tools – in the right hands – can mean healing for more people than ever before. All of these pieces can be mixed and matched to create a full variety of costumes.
