Gavazzi, J. (2026, July).
Psychotherapy Bulletin, 61(4).
Clinical Impact Statement:
Psychologists who integrate AI tools without deliberate attention to their clinical consequences risk producing an illusion of competence: the capacity to generate sophisticated clinical language without the depth of reasoning that the language is meant to reflect. Maintaining the sequencing of independent judgment before AI consultation, treating AI outputs as objects of critical analysis, and preserving documentation as a reflective practice are essential safeguards for the integrity of quality psychological care.
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Practical Recommendations
None of this argues against using AI in psychological practice. LLMs offer genuine value as consultation resources, prompts for critical analysis, and tools for broadening the range of hypotheses a clinician considers. The argument is about sequencing and stance. Several principles follow.
- AI-generated formulations should follow rather than precede independent clinical reasoning. The psychologist who develops her own differential formulation and then consults an LLM to examine what she may have missed is doing something different from the psychologist who queries the LLM first. The first sequence sharpens clinical thinking. The second quietly replaces it. This is a choice worth making consciously rather than letting convenience decide.
- AI-generated outputs should be treated as objects of critical analysis, not as drafts to be refined. Before accepting an LLM’s formulation, ask what it assumed, what it excluded, and how it compares to your own reasoning. This turns an AI interaction into a reflective exercise rather than a shortcut.
