Precision neuropsychology in the area of AI.

This perspective paper introduces the term "precision neuropsychology" to reflect on an approach that integrates AI-driven assessment tools with traditional neuropsychological frameworks-an integration expected to become crucial in future clinical practice. The paper outlines the technological evolution from basic computerized testing to sophisticated machine learning applications that could enable clinicians to more accurately detect subtypes of neuropsychological conditions. Key opportunities include enhanced pattern recognition in traditional assessments (e.g., digital clock drawing), continuous monitoring of symptom fluctuations (e.g., Attention Deficit Disorder), and personalized assessment and treatment procedures based on individual needs (e.g., learning disorders). The paper also addresses critical implementation challenges: ethical considerations including algorithmic bias and data privacy; balancing quantitative AI analytics with qualitative clinical expertise to avoid reductionism; and developing new competencies for neuropsychologists to effectively integrate AI in their research and clinical work. By providing practical implementation guidelines while preserving holistic patient care, precision neuropsychology shows promise for enhancing both diagnostic accuracy and treatment efficacy in neuropsychological practice.