Artificial intelligence (AI) is increasingly transforming healthcare delivery through applications in clinical diagnosis, electronic health records, virtual patient support, telemedicine, predictive analytics, and healthcare administration. This study examines the effects of AI on healthcare delivery in selected cities in South-East Nigeria, with particular attention to AI awareness and utilization, diagnostic AI, chatbot-assisted triage, AI-supported electronic health records, perceived usefulness, perceived ease of use, trust in AI, training, infrastructure readiness, and data privacy concerns. The study adopts a quantitative cross-sectional survey design and is anchored on the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and the World Health Organization digital-health and responsible-AI perspective. The target population comprises healthcare workers, patients, and hospital administrators in Enugu, Owerri, Aba, Awka, and Abakaliki, with a planned sample of 800 respondents drawn from public, private, and teaching hospitals. Data are measured through structured scales covering AI awareness, frequency of AI use, perceived usefulness, perceived ease of use, trust in AI, privacy concerns, training, infrastructure readiness, service-delivery time, diagnostic accuracy, patient satisfaction, and a Healthcare Delivery Index. The analytical framework employs descriptive statistics, correlation, multiple regression, mediation, and moderation analysis. The supplied study parameters indicate that functional AI availability remains limited, higher AI use is associated with shorter service-delivery time, training improves perceived usefulness, and data privacy is a prominent barrier. The study concludes that AI can strengthen efficiency, diagnostic support, and patient experience, but its benefits depend on infrastructure, workforce competence, trustworthy systems, data governance, and human clinical oversight.