Artificial intelligence is moving from pilot projects into core functions of healthcare systems across Egypt and the wider Middle East, reshaping diagnosis, administration and precision medicine. Hospitals are deploying machine‑learning models to assist with CT, MRI and mammogram interpretation, digital pathology, clinical documentation and appointment scheduling, while researchers and clinicians are using AI to analyse genomic data, predict drug interactions and match patients to clinical trials. The shift is occurring as policymakers and providers contend with ageing populations, rising chronic disease burdens and pressures to improve system efficiency. "AI should complement—not replace—clinical judgment," researchers wrote after studying chatbot responses in clinical contexts, a caution echoed across academic reviews of medical AI. That 2023 study published in JAMA Internal Medicine found healthcare professionals preferred chatbot‑generated responses to physicians' written replies in nearly four out of five evaluations of patient questions, with AI responses rated higher for both quality and empathy. Yet a 2025 systematic review in JAMA Network Open highlighted wide variation in how large language models are evaluated for accuracy, safety and clinical usefulness, concluding that standardized validation methods remain limited. Practical applications and early adopters Clinicians in Egypt are reporting concrete AI use cases. At Africa Health ExCon in Cairo in 2025, Dr. Ahmed El‑Bassiouny , Head of the Stroke Unit at Ain Shams University Hospitals, pointed to AI's role across stroke diagnosis, treatment planning and rehabilitation, underscoring how machine learning augments clinician workflows rather than replacing them. Within hospitals, algorithms help prioritise urgent imaging cases and flag subtle abnormalities while decision‑support tools estimate deterioration risk and recommend evidence‑based pathways. Diagnostics: AI assists interpretation of CT scans, MRIs…