AI in CBT Training: What WCCBT 2026 Taught Us About the Future of Therapist Education

When people talk about artificial intelligence in mental health, the conversation often begins with the same question: "Will AI replace therapists?"

After presenting CBT Trainer at the World Congress of Cognitive and Behavioural Therapies (WCCBT) 2026, we found that this wasn't the question clinicians, educators, and supervisors were asking. Instead, the conversations were remarkably practical.

Can AI help trainees practice before working with real clients?
Can it provide structured feedback between supervision sessions?
Can it make high-quality CBT training more accessible?
Can it support educators without replacing them?

These discussions reinforced something we've believed since building CBT Trainer: the greatest opportunity for AI is not replacing therapists — it is improving how therapists are trained.

The Biggest Challenge in CBT Training Isn't Learning the Theory

Most CBT training programs provide excellent theoretical foundations. Students learn cognitive models, behavioural experiments, case conceptualisation, and evidence-based interventions. Yet many trainees still feel underprepared when they begin seeing clients.

The reason is simple: clinical competence develops through repeated, deliberate practice, not from reading textbooks alone. Like learning a musical instrument or mastering a new language, psychotherapy requires continual rehearsal, reflection, and feedback. However, opportunities for realistic practice are often limited by time, supervisor availability, and access to suitable role-play partners.

This gap between knowledge and clinical performance is one of the biggest challenges in psychotherapy education today.

AI Creates More Opportunities to Practice

Throughout WCCBT 2026, we noticed growing interest in how AI could help address this challenge. Rather than asking whether AI should conduct therapy independently, educators were exploring how it could support the learning process.

AI-powered simulated patients can allow trainees to:

practise interviewing skills whenever they choose;
experience a wide variety of clinical presentations;
receive immediate, structured feedback;
repeat challenging scenarios until they gain confidence; and
prepare more effectively before supervision or real client sessions.

Importantly, these tools are not intended to replace supervisors or traditional teaching. Instead, they can expand access to deliberate practice, allowing supervision time to focus on deeper clinical reasoning and professional development.

AI Should Enhance, Not Replace, Clinical Education

One message became clear during our conversations at WCCBT: the future of psychotherapy education is unlikely to be a choice between human supervision and artificial intelligence. Instead, the strongest educational model combines both.

Experienced supervisors provide judgement, clinical wisdom, ethical guidance, and nuanced interpersonal feedback — qualities that remain central to therapist development. AI, meanwhile, offers something equally valuable: unlimited opportunities for practice, consistency, and immediate feedback between supervision sessions.

Together, these approaches can create a richer and more accessible learning experience than either could achieve alone.

Looking Ahead

Presenting CBT Trainer at WCCBT 2026 gave us the opportunity to engage with clinicians, researchers, educators, and training institutions from around the world. While opinions differed on many aspects of AI, there was broad agreement on one point: future therapists need more opportunities to practise, not fewer.

If AI can make deliberate practice more accessible, provide high-quality feedback, and help trainees build confidence before working with real clients, then its greatest contribution may not be changing psychotherapy itself. It may be changing how future psychotherapists learn psychotherapy.

At CBT Trainer, we believe that's where AI can make the most meaningful impact.

Citation: Zhang T, Saunders R, Pilling S, O'Driscoll C. An AI-Driven Virtual Patient Platform (CBT Trainer) for Training Cognitive Behavioral Therapy Practitioners Against Competencies: Mixed Methods Pilot Study. JMIR Med Educ 2026;12:e84091. URL: https://mededu.jmir.org/2026/1/e84091 DOI: 10.2196/84091