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This study explores the feasibility of integrating artificial intelligence (AI) into counsellor training to enhance feedback quality and scalability. Using Natural Language Processing (NLP), simulated counselling transcripts were analysed across three therapeutic modalities: Person-Centred Therapy (PCT), Pluralistic Therapy, and Cognitive Behavioural Therapy (CBT). NLP, a branch of AI that combines computational linguistics and machine learning, enables systems to interpret and generate human language. The researcher, a qualified psychotherapist and educator, constructed simulated transcripts that were anonymously reviewed by colleagues practising in the respective modalities. The fine-tuned NLP system evaluated key therapeutic markers, including empathy, relational depth, cognitive restructuring, and responsiveness to client preferences. It also demonstrated safeguarding potential by detecting linguistic indicators of suicidal ideation. Findings suggest that AI has the potential to identify modality-specific therapeutic elements and provide consistent, actionable feedback aligned with training benchmarks. However, challenges remain in capturing nonverbal cues and ensuring adaptability across diverse contexts and practitioner styles. Ethical integration within reflective, practitioner-led training frameworks is essential. Overall, AI has the potential to augment human supervision by offering timely, structured, and scalable insights, provided its use is ethically governed and firmly embedded within reflective, practitioner-led training frameworks.
Leah Athanassopoulos (Tue,) studied this question.