Artificial intelligence in neuropsychological practice-tool selection, privacy, and billing guidance

Objective: AI is rapidly transforming healthcare, yet its integration into clinical neuropsychology remains limited and uneven. This paper explores the current landscape of AI tools applicable to neuropsychological practice and provides practical guidance for clinicians and trainees on their responsible use. Method: We reviewed ambient scribing technologies, large language models (LLMs), and input-based systems for documentation and report generation, with attention to HIPAA compliance, data privacy, billing implications, and responsible use policies. The evolving regulatory environment and ethical considerations surrounding AI integration into clinical workflows are examined. Conclusions: Neuropsychologists can enhance efficiency and accessibility by adopting AI thoughtfully and transparently while preserving the profession's core values of accuracy, contextualization, and patient-centered care. Practical resources are provided to support implementation in real-world settings, including a decision tree, feature comparison table, and "Guidelines for Responsible Use of AI in Clinical Neuropsychology," with special emphasis on maintaining clinical oversight.