A person wakes in the middle of the night, overwhelmed and needing someone to talk to. But instead of calling a loved one or booking a counseling session, they open ChatGPT.
Around the world, artificial intelligence chatbots are becoming companions, coaches, sounding boards and, for a rising number of people, unofficial therapists.
Studies have found that many users turn to AI to discuss personal struggles, seek emotional support, reflect on their feelings and better understand their mental health.
The appeal is easy to understand. Chatbots don’t judge. Unlike stretched mental health services in countries such as New Zealand and Australia, they don’t keep people on lengthy waiting lists.
But as AI tools become more involved in mental health, it is increasingly important to understand where the technology can genuinely help—and where its limits lie.
Can AI recognize depression?
Today’s chatbots can seemingly do everything—from answering complex questions to offering relationship advice—all while sounding remarkably human and empathetic.
With mental health specifically, research has shown that AI systems can provide helpful information, encourage self-reflection and offer emotional support in some situations.
Some studies even suggest that AI-based mental health tools can help reduce symptoms of anxiety and depression when carefully designed and used appropriately. AI is also beginning to show promise in helping people practice cognitive reframing by encouraging them to consider alternative ways of interpreting difficult situations.
At the same time, researchers, clinicians and regulators have raised serious concerns.
AI systems can generate inaccurate advice—sometimes agreeing with or reinforcing harmful beliefs instead of encouraging people to seek appropriate help—and miss signs of crisis.
An AI system may sound understanding, but it cannot truly understand the person behind the conversation. Unlike mental health professionals, AI is not held to the same professional or regulatory standards if something goes wrong.
More than just providing information, mental health care relies on trust, empathy, clinical judgment and human connection.
All of this is why many experts see AI as a tool to support mental health care, rather than something that can or should replace it.
So where exactly might it have a useful role?
We in the University of Auckland’s 2DN research group have been investigating one interesting application: spotting signs of depression earlier.
Depression often affects how people communicate. Changes in speaking rate, pauses, tone of voice, word choice and emotional expression can provide clues about a person’s mental state.
These are examples of what researchers call “digital biomarkers“—measurable patterns in our behavior or physiology that can provide clues about our health. Researchers are also investigating many others, including facial expressions, sleep patterns and physical activity.
Our work explores whether AI can learn to recognize patterns from both speech and text.
Rather than diagnosing people or replacing clinicians, the goal is to develop tools that support screening and monitoring, helping flag people who may benefit from further assessment.
This is similar to how wearable devices can detect unusual heart activity without replacing a cardiologist. Instead, they provide clinicians with another piece of information to help inform decisions.
AI’s promise and pitfalls
AI might support mental health care in many other ways.
It has the potential to expand access to services, support underserved communities, identify problems earlier and help people better understand and manage their own mental well-being.
It can also reduce barriers to seeking help—and even personalize therapies by adapting support to an individual’s needs when sufficient high-quality data is available.
But with these opportunities come obvious challenges.
Mental health data is among the most sensitive information a person can share. Privacy, security and informed consent must be carefully protected. AI systems can also inherit biases from the data used to train them, potentially affecting how well they work for different populations.
There is also the risk of overreliance. Recent research suggests that people may place too much trust in AI systems, even when the technology is wrong.
Because AI often responds in ways that feel supportive or validating, users may accept its advice without questioning it or seeking professional help. In mental health settings, that trust can have serious consequences.
Still, it is inevitable that AI’s role in mental health—as with all other areas of life—will only grow in the coming years.
Its greatest value may lie in helping people better understand their mental well-being and supporting clinicians in identifying risks earlier.
Technology can recognize patterns. People provide empathy, trust and clinical judgment. The future of mental health care may depend on combining the strengths of both.
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