The Role of AI in Mental Health Therapy: Balancing Innovation and Human Connection
- louisehenderson307
- Jan 3
- 5 min read
Updated: 6 days ago
This blog explores the ethical, practical, and emotional impact of AI in mental health therapy. Discover why human connection, confidentiality, and hybrid approaches are essential for safe and effective digital counselling. Learn how AI can supplement but not replace professional support, and what users should know about privacy and crisis response.
Recent trends show that AI is being used more for mental health reflection than for coding or productivity. This shift raises important questions: What does this mean for therapy, and what are the implications for those seeking support? Imagine if the help you needed was available 24/7, but it wasn’t human. As AI tools become increasingly common as companions and for mental health support, it’s essential to examine both their promise and their risks. From a counselling perspective, this means considering ethical, confidentiality, and safety issues while keeping legal frameworks and the therapeutic relationship at the centre of the discussion.
Why Human Connection Still Matters
At the heart of counselling is the therapeutic relationship. This bond is built on trust, empathy, collaboration, and ethical care. Such a connection allows counsellors to attune to subtle emotions, respond to context, and provide a sense of safety—things that AI cannot replicate at present. While AI can help you reflect, it cannot help you feel what you feel. As Rubin et al. (2024) note,
“Empathy remains a uniquely human strength in therapy. While AI can simulate supportive responses, it cannot genuinely understand or share in a client’s emotional experience.”
Ethical practice relies on human relational depth, confidentiality, and safeguarding.
Confidentiality and Data Protection
Human counsellors must follow strict ethical and legal standards, including GDPR (data protection) in the UK. They must maintain secure, confidential records in line with data protection regulations and ensure that information shared is used appropriately, always respecting client autonomy. In contrast, AI tools may store, process, or use conversations for AI training without gaining consent, depending on individual platform policies. As the Mental Health Foundation (n.d.) cautions,
“Unlike human therapists, AI systems may not guarantee the same level of confidentiality, and users should be made aware of potential data privacy risks.”
The key takeaway is that confidentiality is more robust with human-led counselling, and awareness of AI’s limitations is essential for safe and responsible use.
AI Tools: Strengths and Opportunities
AI offers several benefits for mental health support. It provides 24/7 accessibility for reflection and journaling, allows for private, low-pressure interaction, and encourages self-exploration through generated prompts. These features can help individuals engage with their mental health early on. However, as Cruz-Gonzalez et al. (2025) remind us,
“AI offers unprecedented opportunities for accessible mental health support, but it cannot replace the relational depth and ethical oversight provided by human therapists.”
While AI can complement counselling by providing reflection between sessions, it is not a substitute for professional guidance, especially when it comes to confidential, sensitive, or safeguarding disclosures.
Text-Based Human Services: The Relational Advantage
Human-led text-based services stand out by offering active listening, empathy, crisis detection, and safeguarding. These services are delivered by professionals with training, ethical oversight, and a commitment to strict confidentiality. The key difference is that human services provide relational depth, safety, and legally protected confidentiality. Presently, these are qualities that AI cannot match.
Comparing AI Tools and Human Services
AI tools are available around the clock, while human-led services typically operate during limited hours. Only human services can offer true empathy, crisis intervention, and professional safeguarding. While AI tools are often low-cost or free and provide immediate access, they lack the ability to tailor long-term support and cannot guarantee confidentiality, which is dependent on the individual platform. In contrast, human services offer supportive care with legally and ethically protected confidentiality.
Risks and Ethical Considerations
While AI holds promise for mental health support, it comes with clear limitations and potential dangers. AI cannot attune to subtle emotions or build a therapeutic relationship, which may lead users to substitute AI for real therapy and delay seeking support. In crisis situations, AI cannot reliably respond to suicidal thoughts, self-harm, or severe mental health crises, risking false reassurance or delayed help. As Beg et al. (2024) emphasize,
“The integration of AI in mental health care must be guided by ethical frameworks that prioritise client welfare, confidentiality, and informed consent.”
Over-reliance on AI can lead to avoidance of human support and potential isolation. Additionally, as Ophir et al. (2025) state,
“AI-driven interventions should supplement, not replace, professional mental health care, especially in high-risk or crisis situations.”
From a counselling perspective, the Ethical Framework emphasises that client welfare, competence, safeguarding, and confidentiality must remain central, and AI should only supplement, never replace, professional support.
Pros and Cons at a Glance
The advantages of AI in mental health include immediate, always available access, low or no-cost support, and the ability to reflect privately. This can help people engage with support, reduce barriers, and stigma. However, AI cannot replicate human empathy, ensure safety, or respond to crises/safeguarding, nor can it provide individualised support. There is also a risk of over-reliance, limited confidentiality, and an inability to manage high-risk situations.
Reflection
Can AI safely supplement therapy without undermining the therapeutic relationship?
How can AI reduce barriers while maintaining ethical and confidentiality standards?
What role should counsellors play in guiding responsible AI use?
Could hybrid approaches (AI + human support) increase accessibility while preserving relational depth?
If AI can respond instantly to your anxiety but cannot truly understand you, is it support or a mirror?
The Future of AI and Therapy
AI in mental health is cutting edge but not risk-free. Its potential lies in providing immediate, accessible reflection, reducing stigma for initial engagement, and removing barriers. It can supplement therapy in safe, structured ways. However, as the British Association for Counselling and Psychotherapy (n.d.) suggests,
“The future may lie in hybrid support: AI for reflection, humans for empathy, ethical guidance, and confidentiality.”
Used responsibly, AI can complement human support, not replace it.
Further Reading & References
British Association for Counselling and Psychotherapy (BACP). (n.d.) Ethical Framework for the Counselling Professions. Available at: https://www.bacp.co.uk/events-and-resources/ethics-and-standards/ethical-framework-for-the-counselling-professions/ (Accessed: 3 January 2026).
Mental Health Foundation. (n.d.) Mental Health and Digital Technology. Available at: https://www.mentalhealth.org.uk/publications/mental-health-and-digital-technology (Accessed: 3 January 2026).
Barzkar, F. et al. (2025). The Machine as Therapist: Unpacking Transference and Emotional Healing in AI-Assisted Therapy. Journal of Contemporary Psychotherapy, 55, pp.361–368. Available at: https://link.springer.com/article/10.1007/s10879-025-09677-7 (Accessed: 3 January 2026).
Beg, M.J. et al. (2024). Artificial Intelligence for Psychotherapy: A Review of the Current State and Future Directions. Indian Journal of Psychological Medicine. Available at: https://journals.sagepub.com/doi/pdf/10.1177/02537176241260819 (Accessed: 3 January 2026).
Ophir, Y. et al. (2025). Balancing promise and concern in AI therapy: a critical perspective on early evidence from the MIT–OpenAI RCT. Frontiers in Medicine, 12. Available at: https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1612838/full (Accessed: 3 January 2026).
Cruz-Gonzalez, P. et al. (2025). Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications. Psychological Medicine, 55, e18. Available at: https://www.cambridge.org/core/journals/psychological-medicine/article/artificial-intelligence-in-mental-health-care-a-systematic-review-of-diagnosis-monitoring-and-intervention-applications/04DBD2D05976C9B1873B475018695418 (Accessed: 3 January 2026).
Rubin, M. et al. (2024). Considering the Role of Human Empathy in AI-Driven Therapy. JMIR Mental Health, 11, e56529. Available at: https://mental.jmir.org/2024/1/e56529 (Accessed: 3 January 2026).
Wajid, A. et al. (2025). Applications of artificial intelligence in mental health: a systematic literature review. Discover Artificial Intelligence, 5, article 332. Available at: https://link.springer.com/article/10.1007/s44163-025-00569-2 (Accessed: 3 January 2026).
Ni, Y. & Jia, F. (2025). A Scoping Review of AI-Driven Digital Interventions in Mental Health Care: Mapping Applications Across Screening, Support, Monitoring, Prevention, and Clinical Education. Healthcare, 13(10), 1205. Available at: https://www.mdpi.com/2227-9032/13/10/1205 (Accessed: 3 January 2026).
Humayun, A. et al. (2025). Artificial intelligence as a predictive tool for mental health status: Insights from a systematic review and meta-analysis. PLOS One, 20(9): e0332207. Available at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0332207 (Accessed: 3 January 2026).
Pandey, H.M. (2025). Artificial Intelligence in Mental Health and Well-Being: Evolution, Current Applications, Future Challenges, and Emerging Evidence (A Short Review). arXiv preprint. Available at: https://arxiv.org/pdf/2501.10374 (Accessed: 3 January 2026).
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