The AI Pathologist for Diverse Medical Diagnosis project, led by Heriot-Watt University Dubai, aims to transform pathology diagnostics in the UAE by addressing diagnostic error rates (5–15%), slow image analysis, and pathologist shortages (1:20,000 in some emirates). Over 36 months, we will develop an AI system achieving ≥95% diagnostic accuracy for multiple diseases (e.g., cancers, infections) across imaging modalities (WSI, CT, MRI, ultrasound), reducing turnaround times by 50%, ensuring equitable diagnostics for Dubai’s diverse population, and fostering clinician trust via explainable AI (XAI). Leveraging capsule networks for spatial-aware analysis, foundation models like Virchow for data filtering, and XAI techniques like Grad-CAM for transparency, the project integrates with hospital EHRs using HL7 FHIR standards. The multidisciplinary team, including Dr. Nidhal Abdulaziz, Dr. Mohamed Al-Musleh, Dr. Rehan Ahmed, Prof. Farhad Oroumchian, Prof. Sattar Alshryda, Prof. Ahmed Elserafi, a PhD student, and a research assistant, will collect ≥10,000 anonymized images, develop and deploy the AI system in DHA hospitals, train ≥50 pathologists, and publish ≥3 high-impact papers. Aligned with Dubai’s Health Strategy 2021–2026 and UAE Vision 2031, the project mitigates workforce shortages, reduces errors, and positions Dubai as a global AI healthcare hub by mid-2028. Through fairness audits, it promotes equitable healthcare and UN SDG 3, setting new standards in precision medicine with potential applications in radiology and beyond.