I’ve worked in mental health for decades and I think AI could save some young people

OpinionResearcher in clinical psychiatryOctober 11, 2026 — 4:30pmOctober 11, 2026 — 4:30pmI’ve worked clinically in mental health and suicide prevention for the better part of four decades. And I now believe the emergence of generative AI could be the most positive opportunity to ever emerge in the field.I know that sounds jarring. The potential for chatbots to harm those experiencing mental health issues has been widely canvassed. Chatbots can promote engagement with sycophantic interactions that support harmful behaviour. They can also state falsehoods or dismiss warning signs clinicians would catch.Young people could get valuable mental health support from chatbots. Aresna VillanuevaGiven this, some are keen to stuff the AI genie back in the bottle. But young people who don’t want to consult a human or can’t make contact for practical reasons are turning to chatbots in droves. They function 24/7 in any location. When someone is desperate at 3am in a remote community, empathic and evidence-informed help is now available in a variety of commercial and other forms.Now, I’m not suggesting that turning to a generic LLM like ChatGPT or Claude for mental health care is always a good option. But I’m also not suggesting that we should accept the outcomes our current youth mental health system is delivering.Previous Brain and Mind Centre research showed youth care services are fragmented and poorly co-ordinated. Those in greatest need are often the most neglected. We also know the story isn’t necessarily much better for those who attend primary care-based early intervention services. In fact, our 2021 research showed nearly two-thirds of those attending these services found their daily functioning – think attending work or school regularly – stayed poor or got worse.So what are we getting wrong? Well, by practical necessity, most traditional mental health care systems have relied heavily on fairly blunt diagnostic concepts and broad averages to allocate care. But AI opens up exciting new alternatives.We can now, for example, use smart tools to implement outcome-based care. Young people can effortlessly record and report their mood, sleep, activity or other symptoms, risk behaviours and level of functioning. With privacy and confidentiality strongly respected, we can then use this data to make critical adjustments to treatments we might otherwise have missed.Recording data has been available for some time – but the “intelligence” of AI adds something extraordinarily useful into the mix. Young people don’t neatly summarise their experiences in conventional diagnostic categories or the reductionist language intrinsic to questionnaires. They might say they’re “wired” or that their brain “zaps” and “goes burr” or is “full of noise”. They might have been on a crowded bus and “freaked out” or had a “meltdown”.A smart language-based model trained on real clinical encounters and genuine research-based evidence, can process a complex human conversation and turn it into the structured information a clinician needs. Research is under way to see if this could also prompt less-skilled clinicians to make more specific inquiries that guide decision-making.This kind of guided information-acquisition could turbocharge the capacities of youth services. A well-calibrated AI assistant could not only prompt primary-care clinicians and less-skilled youth workers, but bring much of the experience of specialised psychiatrists, mental health nurses and clinical psychologists into the room with the young person. This really matters in our outer urban, rural or remote areas where few specialists are available.Most experienced clinicians agree face-to-face assessment and ongoing care are superior to digitally enhanced services. Being able to observe key mental state features and participate in social interactions definitely has its upside. But we should also be brave enough to step back and ask ourselves if face-to-face is always the gold standard. Human interactions are far less consistent than we like to admit. Human judgment is strongly value-laden. When highly trained clinicians assess the same young people independently, they often come to quite different conclusions – not only about diagnosis, but also about treatment or need.I’m not suggesting AI-assisted care is free from its own biases. It’s why some of us are so interested in building and training our own models, and making their assumptions transparent and contestable. But if we’re serious about assisting many more young people, particularly early in the course of their difficulties, we can’t demand immediate perfection. We judge lane-keeping technology in cars by whether it makes a crash less likely. Nobody demanded that it make crashes impossible before we started installing it.I’m sympathetic to those worried about the potential harms of AI on youth mental health. When politicians of good faith like Kate Chaney call for the under-16 social media ban to be extended to chatbots, I understand the appeal. But sweeping bans have the potential to do more harm than good. Because custom AI-driven tools, created for youth mental health, could fundamentally change the game for those in greatest need.Ian Hickie is co-director, health and policy, at the Brain and Mind Centre, University of Sydney, and a former national mental health commissioner. The Brain and Mind Centre is currently in a mental health research collaboration with AI company UNCAPT. The Opinion newsletter is a weekly wrap of views that will challenge, champion and inform your own. Sign up here.Lifeline 13 11 14Kids Helpline 1800 55 1800.Ian Hickie is the co-director, health and policy at the Brain and Mind Centre, University of Sydney, and a former national mental health commissioner.From our partners