Artificial intelligence tools such as chatbots are becoming common in everyday life. Some people use them to ask questions about mental health, reflect on emotions, or look for coping ideas. Research on this topic is still developing. Some early studies suggest that certain structured mental health chatbots may help reduce short-term distress for some users. At the same time, experts emphasize that AI tools have important limits and should not replace professional care.
This guide explains what AI may be able to do, where risks can arise, and how to use these tools more carefully if you choose to use them.
Important: AI tools are not a substitute for psychological assessment, diagnosis, psychotherapy, crisis care, or medical treatment.
What AI May Be Able to Help With
What research suggests:
A systematic review and meta-analysis published inย Digital Medicineย examined studies of conversational AI tools designed for mental health support. Some trials found small reductions in symptoms such as depression or distress in the short term. The same research found no clear improvement in overall psychological well-being and emphasized the need for more long-term evidence.
These studies mainly examined structured mental health chatbots that delivered specific exercises or educational material. There is much less research on general-purpose AI systems used informally for emotional support.
What this means for patients:
If you choose to use AI, it may be more useful for reflection and organization than for decision-making. For example, some people use AI tools to
โข organize thoughts before speaking with a therapist
โข turn notes into a list of concerns to discuss in treatment
โข generate journaling prompts or reflection questions
โข summarize information from trusted mental health resources
These activities involve reflection rather than diagnosis or treatment decisions.
Important Risks and Limits
AI tools can sound supportive and knowledgeable. However, they have important limitations that patients should understand.
Privacy and confidentiality
What research suggests:
Studies of digital health tools show that concerns about privacy and data security strongly affect whether people trust and use them. In Canada, health technology assessments have also identified privacy, consent, and data use as major issues in the adoption of AI in health care.
Information entered into AI tools may be stored or analyzed depending on the platformโs policies. These systems do not provide the same legal confidentiality protections that apply to psychotherapy.
A real-world example illustrates this concern. In 2023, the U.S. Federal Trade Commission issued a final order against the mental health platform BetterHelp after allegations that sensitive health information had been shared with third parties for advertising.
Practical tip:
Before entering personal information, ask yourself whether you would be comfortable if that information were stored or shared.
Avoid entering identifying details such as names, addresses, workplaces, or legal matters unless you clearly understand the platformโs privacy policies.
Errors and misinformation
AI systems generate responses by predicting patterns in text rather than verifying facts in the way humans do. As a result, they can produce answers that sound confident but contain inaccuracies.
Canadian health technology assessments note that public trust in AI can be affected by concerns about errors, bias, and misinformation.
Practical tip:
Do not rely on AI as the only source for important information about
โข diagnosis
โข medication
โข safety concerns
โข trauma or abuse
โข legal decisions
For important questions, check the information with a qualified professional or a reliable health organization.
Crisis and safety limits
Research evaluating AI responses to suicide-related questions has found inconsistent performance. In some studies, chatbots showed variability in how they responded to situations involving possible suicide risk.
Because of these limitations, professional organizations advise that AI tools should not be relied on as a stand-alone support in situations involving safety concerns.
If you are experiencing thoughts of harming yourself, feel unable to stay safe, or your mental health is rapidly worsening, contact a crisis line, emergency service, or qualified professional rather than continuing to interact with an AI tool.
Bias and missing context
Health technology assessments also highlight risks related to data quality and bias in AI systems. Research has found that some AI models may show bias in how they interpret or respond to mental health scenarios.
AI tools may not fully recognize the social and personal context that shapes mental health experiences, including factors such as culture, identity, trauma history, disability, discrimination, or financial stress.
Because of this, advice generated by AI may sometimes feel generic or poorly suited to your situation.
Overreliance
Some studies suggest that people may use AI systems for companionship, emotional validation, or guidance about personal decisions. Researchers have noted that this can sometimes lead to emotional overreliance or social isolation.
AI responses can feel supportive, but they do not involve genuine understanding or responsibility in the way human relationships do.
Practical tip:
If you notice that you are relying on AI as your main source of emotional support or repeatedly asking it for reassurance, it may be helpful to step back and seek support from people in your life or from a professional.
Using AI More Carefully
If you decide to use AI tools, keeping their role small and limited may reduce some risks.
Practical guidelines
โข Use AI mainly for reflection or organizing thoughts
โข Avoid entering sensitive personal information
โข Verify important advice with reliable sources
โข Notice how the interaction affects your mood or behaviour
If you feel more confused, more anxious, or more dependent after using AI tools, consider limiting their use.
When to Seek Professional Help
AI tools cannot replace professional mental health care. Seek assessment from a qualified professional if
โข symptoms persist or worsen
โข problems interfere with daily functioning
โข safety concerns arise
โข you feel stuck or uncertain about what to do next
Mental health professionals can provide individualized assessment, clinical judgment, and evidence-based treatment.
Final Note
AI tools may sometimes assist with reflection or information seeking, but current research shows important limitations and safety concerns. When mental health problems are persistent, complex, or worsening, support from qualified professionals remains essential.
References
Alhammad, N., Alajlani, M., Abd-Alrazaq, A., Alsaad, R., Abuhamdah, S., Al-Hadithi, T., Al-Huwail, D., Alhuwail, D., Al-Khalifa, K., & Househ, M. (2024). Patientsโ perspectives on the data confidentiality, privacy, and security of mHealth apps: A systematic review. Journal of Medical Internet Research, 26, e50715. https://doi.org/10.2196/50715
Canadian Agency for Drugs and Technologies in Health (CDA-AMC). (2025). 2025 watch list: Artificial intelligence in health care. https://www.cda-amc.ca
Federal Trade Commission. (2023). FTC gives final approval to order banning BetterHelp from sharing sensitive health data for advertising, requiring it to pay $7.8 million. https://www.ftc.gov/news-events/news/press-releases/2023/07/ftc-gives-final-approval-order-banning-betterhelp-sharing-sensitive-health-data-advertising
Li, H., Zhang, R., Lee, Y.-C., Kraut, R. E., & Mohr, D. C. (2023). Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being.ย Digital Medicine, 6, 236.ย https://doi.org/10.1038/s41746-023-00979-5
Linardon, J., Fuller-Tyszkiewicz, M., Firth, J., Goldberg, S. B., Anderson, C., McClure, Z., & Torous, J. (2024). The reporting and incidence of adverse events in clinical trials of mental health apps: Systematic review and meta-analysis. npj Digital Medicine, 7, 363. https://doi.org/10.1038/s41746-024-01388-y
Luo, X., Wang, Z., Tilley, J. L., Balarajan, S., Bassey, U.-A., & Cheang, C. I. (2025). Seeking emotional and mental health support from generative AI: Mixed-methods study of ChatGPT user experiences. JMIR Mental Health, 12, e77951. https://doi.org/10.2196/77951
McBain, R. K., Cantor, J. H., Zhang, L. A., Baker, O., Zhang, F., Burnett, A., Kofner, A., Breslau, J., Stein, B. D., Mehrotra, A., & Yu, H. (2025). Evaluation of alignment between large language models and expert clinicians in suicide risk assessment. Psychiatric Services, 76(11), 944โ950. https://doi.org/10.1176/appi.ps.20250086
World Health Organization. (2025). Ethics and governance of artificial intelligence for health: Guidance on large multi-modal models. World Health Organization. https://www.who.int/publications/i/item/9789240084759
This guide was developed and reviewed by Dr. Joachim Sehrbrock. Artificial intelligence (OpenAI, 2026) was used to assist with drafting and editing of this guide.