Neuropsychology has long relied on standardized assessments and expert clinical judgment to diagnose and treat cognitive disorders. However, these traditional methods face inherent limitations, including variability in clinician expertise, test-retest reliability concerns, and the challenge of capturing real-time cognitive fluctuations. As the field advances, artificial intelligence (AI) is emerging as a transformative force, offering new ways to personalize neuropsychological assessments and interventions. This presentation explores how AI-driven insights are revolutionizing neuropsychology, moving beyond static assessments to dynamic, adaptive, and patient-centered care. One of AI’s most promising applications is its role as a smart supervisor in mental health practice. By analyzing vast amounts of cognitive, behavioral, and physiological data, AI can detect subtle patterns that might escape human observation. An AI-driven system that provides real-time decision support, enhancing clinicians’ ability to make accurate and timely diagnoses is going to be presented. Moreover, this AI-powered model can continuously learn and refine its recommendations, allowing for personalized assessments that evolve based on an individual’s cognitive trajectory. 

This adaptability is particularly valuable for tracking neurocognitive changes over time, making AI a powerful tool in early detection and intervention for conditions such as Alzheimer’s disease, ADHD, and traumatic brain injuries. This approach not only improves patient outcomes but also optimizes clinician workflow, reducing decision fatigue and administrative burden. However, integrating AI into neuropsychology comes with ethical and clinical considerations. Transparency, explainability, and clinician oversight are critical to ensuring responsible AI use. As AI continues to evolve, it has the potential to make neuropsychological care more accessible and efficient. AI-driven neuropsychology platforms could bridge gaps in healthcare accessibility, bringing high-quality cognitive assessments and interventions to remote and underserved populations. Furthermore, the integration of AI in clinical research could accelerate discoveries in neurocognitive disorders, leading to breakthroughs in personalized medicine.