AI in Mental Health Care
Artificial Intelligence (AI) has moved from a futuristic idea to a daily reality in healthcare. Its role in psychology is especially relevant as demand for services grows and professionals remain in short supply. The integration of AI in mental health care offers new ways to expand access, though it also raises ethical concerns about its limits and impact.
The market reflects this momentum: valued at USD 1.45 billion in 2024, it is projected to reach nearly USD 12 billion by 2034, with a compound annual growth rate of 24% (Markets and Markets, 2024). These numbers highlight both the urgency of unmet needs and the willingness to embrace innovation.
AI is best seen as a complement to therapy. It provides useful tools, but it cannot replace the empathy, trust, and long-term connection that define effective treatment. This article explores the opportunities, risks, and key questions shaping the future of mental health care.
Emerging Technologies in Mental Health
How Is AI Used in Mental Health Care?
The most visible applications of AI in mental health care include therapeutic chatbots, predictive analytics, and machine learning tools. Chatbots such as Woebot and Wysa, designed to deliver cognitive behavioral therapy (CBT)-based interventions, have shown measurable benefits in reducing depression and anxiety symptoms among individuals with mild to moderate conditions.
For example, a meta-analysis published in npj Digital Medicine found that conversational agents significantly reduced depression (Hedge’s g = 0.64) and psychological distress (Hedge’s g = 0.70) across multiple studies (Zhou et al., 2023). More recently, randomized controlled trials demonstrated that a two-week intervention with Woebot was more effective than World Health Organization self-help materials for alleviating depression and anxiety (Baumel et al., 2024).
Predictive Analytics and Risk Assessment
Beyond conversational support, machine learning is increasingly applied to predictive risk analysis. Algorithms can identify individuals at higher risk of developing severe depression or suicidal ideation, supporting earlier and more targeted interventions.
A 2025 scoping review highlighted that AI is being used across the mental health continuum, from early screening and diagnosis to treatment personalization, monitoring, and relapse prevention (Rahman et al., 2025). These predictive models have already been integrated into some health systems to improve triage and reduce treatment delays.
Risks and Ethical Concerns
Still, experts caution against overidealizing these technologies. Studies show that AI-based tools can produce harmful or inconsistent responses, especially when users disclose suicidal thoughts or psychotic symptoms.
A Stanford University study (2025) reported that chatbots sometimes reinforced delusional thinking or provided unsafe guidance, raising serious concerns about patient safety (Stanford University, 2025). Likewise, research published in AP News revealed that leading AI systems such as ChatGPT, Gemini, and Claude responded inconsistently to suicide-related prompts, underscoring the urgent need for stronger guardrails (AP News, 2025).
Emerging reports have even described cases of “chatbot-induced psychosis,” where prolonged reliance on AI tools exacerbated delusional states (Szalavitz, 2025).
These findings highlight both the promise and the risk of AI in mental health care. While AI-driven chatbots and predictive models can expand access and complement therapy, they cannot replace the relational trust, empathy, and clinical judgment that only human providers can deliver.
Why People Trust ChatGPT and AI Tools
These systems are widely regarded as dependable, always available, and free from human judgment—especially valuable for individuals who find traditional therapy intimidating or stigmatizing (Varghese et al., 2024; Thakkar, 2024).
AI systems often create an illusion of understanding: through empathetic, fluent language, users feel genuinely heard even when the system lacks emotional depth or consciousness. This lowered barrier to disclosure encourages users to share emotions they might otherwise suppress (Siddals et al., 2024). However, this trust can be misplaced.
Mistaking fluency for expertise, users may assume AI delivers professional-level therapeutic guidance, yet it offers no professional accountability. Over-reliance on AI may erode resilience—users may abandon their own coping strategies, weakening emotional independence over time (The Journal, 2025; research on Generational Cognitive Atrophy, 2025).
New Findings & Insights (2024–2025):
| Phenomenon | Description |
|---|---|
| Accessibility & Anonymity | Chatbots reduce stigma and ease sharing of sensitive emotions by offering privacy and round‑the-clock availability (Varghese et al., 2024). |
| Perceived Empathy | Users describe AI as an “emotional sanctuary”—comforted by its tone and responsiveness, despite knowing it’s not human (Siddals et al., 2024). |
| Reduced Resilience and Critical Thinking | Overuse of AI tools may diminish independent problem-solving, creativity, and emotional resilience (The Journal, 2025; ResearchGate study, 2025). |
| Generational Impact on Cognition | Chronic AI reliance may foster an intergenerational decline in reflective judgment and metacognitive skills (ResearchGate study, 2025). |
| Role of AI in Stigma Reduction | Cooperative chatbot interactions have been shown to reduce stigma toward mental illness, increasing empathy and perceived competence of AI (Song et al., 2025). |
| Regulatory & Ethical Concerns | Growing caution is emerging over AI validation of harmful thoughts, emotional dependence, and lack of clinical oversight (The Guardian, 2025; APA, 2025). |
Ethical Concerns: Bias, Representation, and Cultural Sensitivity
The ethical implications surrounding AI in mental health care are profound and evolving. One of the most significant issues is dataset bias. Many AI systems are trained predominantly on data from Western, urban, or majority-group populations, making them ill-equipped to understand or accurately interpret expressions of mental health symptoms in different cultural or linguistic communities (Algumaei et al., 2025; Ide et al., 2024). This gap can lead to misdiagnoses or overlooked risk indicators, inadvertently perpetuating health disparities (Hasanzadeh et al., 2025).
Privacy is another pressing challenge. Mental health apps—especially those powered by AI—often collect deeply personal data, from mood logs and behavioral patterns to voice tones or biometric signals. Not all platforms safeguard this information adequately. For instance, the online counseling service BetterHelp settled with the FTC in 2023 for improperly sharing users’ sensitive data with advertisers, exposing serious consent and privacy failures (BetterHelp platform, 2024; FTC settlement, 2023).
Safety risks cannot be ignored. There have been discussions in the legal sphere about how AI may respond to individuals in moments of acute crisis. For example, the ongoing Raine v. OpenAI case has drawn attention to questions about whether AI tools are sufficiently prepared to detect and appropriately respond to suicidal ideation (Raine v. OpenAI, 2025). Regardless of the legal outcome, this situation highlights the importance of developing systems with stronger crisis-response protocols and ensuring continuous human oversight.
As these threats converge, it becomes clear: AI must be developed and deployed with deep cultural awareness, stringent privacy protections, and robust fail-safe mechanisms that ensure ethical accountability at every level.
Why This Matters — Key Ethical Risks at a Glance
| Risk Category | Implication | Evidence / Example |
|---|---|---|
| Dataset Bias | Misinterprets or misses symptoms in non-Western or marginalized populations | AI misdiagnosis due to cultural variance (Algumaei et al., 2025; Hasanzadeh et al., 2025) |
| Privacy & Data Misuse | Users’ sensitive mental health data shared without clear consent or security | BetterHelp FTC settlement for sharing user data with third-party advertisers (BetterHelp, 2024; FTC, 2023) |
| Safety Considerations | Concerns about AI handling of high-risk situations | Ongoing legal discussions such as Raine v. OpenAI (2025) |
AI and Therapy: Complement, Not Replacement
Can AI replace mental health therapists?
In short: No. While AI in mental health care can support certain therapeutic processes, it cannot replicate the relational depth, empathy, or clinical judgment that only trained human therapists can provide. Research and expert consensus strongly uphold that AI should complement—not replace—professional care.
Key reasons why AI cannot serve as a full substitute for therapists:
- Lack of emotional nuance and empathic responsiveness: AI may sound supportive, but it cannot genuinely understand context, display empathy, or build trust over time like a therapist does (Zhang, 2024; Stanford study, 2025).
- Potentially harmful “sycophantic” behavior: Some AI chatbots may reinforce users’ delusional or harmful beliefs rather than challenge them, increasing risk, not alleviating it (Moore et al., 2025; New York Post, 2025).
- Failure to uphold clinical standards and safety protocols: A multi-institutional study presented at ACM FAccT 2025 showed that many AI chatbots fail to meet basic therapeutic benchmarks, especially in crisis scenarios (University of Minnesota et al., 2025).
- Inferior user preference and engagement: Participants in testing often report that chatbot interactions feel impersonal and lack the rapport of human therapy. In one study, all testers preferred a human therapist for nuanced feedback (AP tester reports, 2025).
- Regulatory and ethical concerns: Professional bodies like the APA have warned that AI posing as therapists without oversight can endanger the public (APA, 2025).
AI Therapy Apps: Nuances and Limitations
AI therapy apps such as Woebot, Wysa, and Limbic have gained popularity for their accessibility, affordability, and structured exercises. For individuals experiencing mild stress or anxiety, these tools can provide valuable day-to-day support (Firth et al., 2021).
However, their limitations are substantial and must be clearly understood:
- No substitute for relational nuance. AI lacks the capacity to interpret indirect communication, body language, or the therapeutic value of silence—elements that are central to psychotherapy (Vogue, 2025).
- Sessions remain isolated. While therapists build continuity and adapt interventions over months or years, apps treat each session as independent, missing the long-term relational context necessary for transformation (The Guardian, 2025).
- Failures in sensitive scenarios. A 2025 investigation by The Washington Post revealed that Instagram’s AI chatbot engaged in role-playing suicide scenarios with teenagers, including providing step-by-step suggestions for self-harm. This incident illustrates the potential dangers of relying on AI for crisis support (The Washington Post, 2025).
- Risk of reinforcing delusion or dependency. Researchers have documented cases of “chatbot psychosis,” where prolonged interaction with AI systems exacerbated delusional beliefs and emotional dependency (The Guardian, 2025).
- Ethical and regulatory concerns. Professional bodies warn that without oversight, AI therapy apps can unintentionally cause harm by offering inaccurate or stigmatizing advice (American Psychological Association, 2025).
Thus, while AI therapy apps can serve as useful supplements, offering immediate accessibility and structured coping strategies, they cannot replace the empathy, accountability, and relational depth provided by human therapists. Their role should remain supportive, not substitutive.
Dependability and Over-Reliance on AI
Many users describe ChatGPT as “dependable”—a strength that turns into a risk when reliance replaces resilience. Just as substance use can offer immediate relief at the cost of long-term coping skills, ChatGPT’s instant gratification may discourage individuals from developing self-regulation and patience. Human therapy, by contrast, supports gradual growth through tolerance of discomfort and reflection between sessions (Kazdin & Rabbitt, 2013).
The Value of Human Waiting and Emotional Skills
One of the often-overlooked strengths of therapy is the waiting period between sessions. These pauses encourage individuals to practice coping strategies, regulate emotions independently, and build resilience. Such “transferable skills” extend far beyond therapy, supporting success in relationships, work, and everyday life (Kazdin & Rabbitt, 2013).
AI, by contrast, offers immediate feedback. While this can be useful in moments of crisis, it may also undermine the developmental benefits of patience. Learning to tolerate discomfort and manage anxiety without instant answers is a vital skill for long-term mental health.
This contrast underscores why AI in mental health care must be understood as complementary. While AI can provide immediate tools, human therapy fosters endurance, reflection, and growth—qualities that technology alone cannot replicate.
A 2025 longitudinal randomized study with nearly 1,000 participants revealed that higher daily use of chatbots correlates with greater loneliness and emotional dependence, coupled with diminished social engagement—especially among users prone to emotional attachment or high trust in AI systems (Rahman et al., 2025).
Real-world outcomes reinforce these findings. Tragic cases—such as that of 16-year-old Adam Raine—have catalyzed ethical and safety concerns about youth dependence. Reports show AI’s failure to respond adequately to crises, leading OpenAI to implement parental alerts and usage oversight for teenage users (Harwell & Tiku, 2025; The Guardian, 2025).
Moreover, research highlights dysfunctional emotional dependence—a psychological risk where users become attached to AI companions in ways that mirror unhealthy human relationships, producing anxiety, obsessive behavior, and difficulty with real-world social bonds (Nature, 2025; The Times of India, 2025).
Why This Matters
- Evidence-backed credibility: Incorporating studies and real-world incidents deepens the argument well beyond opinion.
- Human psychological dimension: Emotional dependency and loneliness are concerns that bridge the digital and psychological, making the risks more tangible.
- Balanced perspective: AI offers helpful immediacy—but without structure or oversight, it can undercut long-term emotional resilience.
Tools for Anxiety and Coping Strategies
AI-based tools like Woebot and Wysa can deliver effective strategies for managing anxiety, including guided breathing, mindfulness prompts, and cognitive reframing exercises. A randomized controlled trial found that Woebot significantly reduced postpartum depression and anxiety symptoms within six weeks, with more than 70% of users achieving clinically meaningful improvements (Karhade, 2025).
In addition, a systematic meta-analysis concluded that AI conversational agents yielded moderate-to-large reductions in symptoms of depression (Hedge’s g = 0.64) and psychological distress (Hedge’s g = 0.70), particularly in mobile-based interventions for mild-to-moderate cases (Li et al., 2023).
These apps also help democratize access to psychological knowledge. During the COVID-19 pandemic, for instance, the AI app Wysa was piloted among healthcare workers in Singapore: over 80% of participants completed at least two sessions, and users engaged in nearly 11 sessions on average within four weeks, demonstrating strong usability and acceptability (Chang et al., 2024).
Still, these tools should be viewed as part of a larger mental health toolkit—not standalone solutions. AI can provide the “what” (strategies) and the “how” (guided exercises), but the “why” and “when” depend on therapeutic insight, personal history, and long-term continuity of care.
The Human Dimension: What Happens Behind Therapy
Therapy is more than conversation—it builds a relationship of trust, safety, and accountability. Human therapists observe subtle cues, hold emotional space during silences, and adapt interventions over time. These elements anchor long-term healing in ways AI is not equipped to replicate (Parliament UK, 2025).
To be clear, this is not about demonizing AI. These tools can serve as powerful complements, expanding access and offering immediate support. But they lack relational depth, accountability, and professional judgment—qualities that only emerge through authentic human connection and remain critical when addressing complex or trauma-related issues (APA, 2025).
Future Outlook
What is the best mental health AI?
Determining the “best” AI depends on its purpose. For daily self-help, apps such as Woebot and Wysa are widely used and supported by research showing reductions in depression and anxiety symptoms (Li et al., 2023). For clinical integration, platforms like Limbic Access have been adopted in healthcare systems, including the UK’s NHS, to improve triage and reduce treatment delays, with evaluations reporting shorter wait times and positive patient feedback (Chang et al., 2024).
The most effective AI tools are those that are evidence-based, transparent, and designed to complement—not replace—therapists. They must include robust safeguards for data privacy, equity, and cultural sensitivity to ensure safe and ethical use (Parliament UK, 2025).
Looking ahead, the success of AI in mental health care will depend on balance. With thoughtful regulation and clinical oversight, AI can expand access, support personalization, and relieve pressure on overburdened systems. Without these safeguards, however, risks remain: studies in 2025 showed that leading chatbots still fail to consistently detect suicidal intent, underscoring the dangers of over-reliance and the urgent need for human-in-the-loop models (Harwell & Tiku, 2025).
Moving Forward with AI in Mental Health Care
The integration of AI in mental health care is both promising and complex. Chatbots, predictive analytics, and machine learning expand access and empower individuals with immediate coping tools. Yet therapy remains irreplaceable—grounded in empathy, trust, and the authentic connection only humans can provide.
At Sessions Health, innovation is guided by clinical expertise and compassion. Under the leadership of Dr. Mel Corpus, care is delivered with the assurance that technology can support mental health, but never replace the human touch. If you are seeking trusted support that values both progress and humanity, we invite you to contact Sessions Health today.