Emotional Intelligence in AI-Mediated Neurology: A Narrative Neurocognitive Review

Ignacio Bonasa Alzuria

Abstract

Artificial intelligence (AI) is rapidly moving from the periphery to the core of neurological practice, including image interpretation, risk stratification, cognitive screening, remote monitoring, and patient-facing communication. This technological transition creates a paradox: as algorithms become more proficient at detecting patterns, the distinctly human ability to recognize, interpret, regulate, and ethically respond to emotion becomes more rather than less important. This narrative review examines the importance of emotional intelligence (EI) in an AI-mediated world from a neurocognitive and neurological perspective. A targeted search of PubMed and Google Scholar was undertaken for English-language literature published between January 2020 and March 2026, with priority given to systematic reviews, meta-analyses, consensus statements, and clinically relevant studies in neurology, medicine, psychiatry, and digital health. Current evidence places EI within distributed brain systems involving the amygdala, insula, anterior cingulate cortex, and multiple prefrontal regions that support emotion recognition, salience assignment, ambiguity processing, selfregulation, and social cognition. In neurological care, EI is especially relevant because dementia, stroke, traumatic brain injury, Parkinson’s disease, epilepsy, and other brain disorders often affect emotion recognition, empathy, insight, and caregiver relationships. At the same time, AI systems can simulate empathic language, improve access, and reduce administrative burden, but they may also encourage cognitive offloading, relational depersonalization, bias opacity, and overtrust in fluent outputs. We argue that EI should be treated as a trainable neurobehavioral competency and a clinical safeguard in the AI era. The future of humane neurology will depend not only on more accurate algorithms, but on clinicians, patients, and institutions that can combine AI literacy with emotional wisdom, reflective judgment, and ethical accountability.