Artificial intelligence in healthcare administration: A survey databased assessment of adoption, barriers, and opportunities in Nigeria

Abstract

Artificial intelligence is reshaping healthcare administration, yet adoption in Nigeria remains low due to several factors including infrastructural and policy gaps. This study among others examined willingness to use and factors influencing AI uptake among health workers using the UTAUT framework. A cross-sectional survey was conducted among 200 healthcare staff across public and private facilities using a structured questionnaire. Data were analyzed with SPSS using descriptive and logistic regression methods guided by the UTAUT framework. AI adoption in Nigerian healthcare administration is highest for records management (74%), scheduling (61%), and billing (54%), while workforce allocation (43%) and supply chain (47%) lag. Structural barriers such as limited digital infrastructure (42%), high implementation costs (40%), and insufficient technical expertise (41%) constrain adoption, yet most respondents (71%) recognize AI’s potential to improve efficiency and reduce administrative costs. Little over 70% were willing to use AI tools in their daily work. Adopting AI is crucial for enhancing efficiency, accuracy, and equity in healthcare administration. To achieve this, investments in digital infrastructure, targeted training, supportive policies, and institutional backing are recommended to overcome structural barriers and maximize AI’s administrative benefits. Keywords: AI Adoption, AI Tools, Barriers, Health Administration, UTAUT Framework.

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