AI Resilience Report forClinical Neuropsychologists

Right now, AI is mostly helping clinical neuropsychologists rather than replacing them. In a December 2025 commentary, the American Board of Professional Psychology explains that generative AI is poised to speed up the most time-consuming parts of a neuropsychological evaluation, especially test administration and scoring, test development, and training simulations, with the goal of reducing examiner burden while keeping the clinician central for data integration and interpretation. That matters because there are fewer than 6,000 clinical neuropsychologists practicing in the U.S. and traditional evaluations involve several hours of standardized testing, hand scoring, and long report writing.

The American Academy of Clinical Neuropsychology's Disruptive Technology Initiative ^[1] similarly notes that AI can reduce diagnostic errors, triage cases, and automate the scoring of thousands of Rey Complex Figure and clock drawings so clinicians can spend more time helping patients directly. A 2026 commentary in the Journal of Clinical and Experimental Neuropsychology ^[2] frames this moment as an "AI inflection point," warning of real risks around safety, privacy, diagnostic bias, "erosion" of clinical judgment, and a lack of transparency — but not as a displacing force.

Adoption is accelerating in medicine overall: Doximity's 2026 State of AI in Medicine Report (via Barchart) ^[3] found that AI use rose from 47% of physicians in April 2025 to 63% by January 2026, with neurologists leading all specialties at 64% adoption, while 71% still cite accuracy and reliability as their top concern. In psychology specifically, a PAR industry outlook ^[4] reports that AI is moving from experimental pilots to everyday workflows in 2026, with psychologists valuing it for streamlining scoring and report writing when transparency and best practices are followed. Adoption is likely to move faster than average because the economic pull is strong — long wait lists, chronic workforce shortages, and heavy paperwork all make labor costs high relative to software.

But adoption will also be slowed by real guardrails: test-security rules protecting copyrighted stimuli, HIPAA privacy, and forensic/legal use of reports mean vendors must build clinician-oversight features. A 2026 review in the Journal of Neuropsychology ^[5] similarly emphasizes cautious, evidence-based integration. The human skills that stay valuable — clinical judgment, empathetic interviewing, and integrating brain, behavior, and life context — are exactly the parts AI is not replacing.