Olawade, David ORCID: https://orcid.org/0000-0003-0188-9836, Clement David-Olawade, Aanuoluwapo, Rotifa, Oluwayomi B. and Wada, Ojima Z. (2025) Artificial intelligence in Nigerian nursing education: Are future nurses prepared for the digital revolution in healthcare? Nurse Education in Practice, 87. p. 104511.

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Abstract

Aim/Objective

This study aims to assess the knowledge, exposure, and willingness of Nigerian nursing students to integrate artificial intelligence (AI) into healthcare, identifying gaps that may hinder its adoption.

Background

AI is revolutionizing healthcare through improved diagnostics, predictive analytics, and automated administrative processes. However, research on AI awareness and adoption among nursing students in low- and middle-income countries (LMICs), particularly in Nigeria, remains limited. Understanding the preparedness of future nurses for AI integration is crucial for optimizing healthcare delivery and education.

Design

A cross-sectional study design was employed to evaluate AI knowledge, exposure, and adoption readiness among nursing students in Nigeria.

Methods

The study involved 676 nursing students from five universities in Nigeria. A structured questionnaire was administered to assess sociodemographic characteristics, AI knowledge, exposure to AI facilities, and willingness to adopt AI technologies. Data were analyzed using descriptive and inferential statistics with Microsoft Excel and JASP 0.19. Associations were tested using ANOVA and Chi-square tests at a 95 % confidence interval (p < 0.05).

Results

Findings revealed that 98 % of students had low AI knowledge, with only 1.8 % demonstrating average knowledge and 0.15 % showing high knowledge. Despite this, 85.5 % were willing to take AI training, and 92.6 % believed AI could enhance healthcare workflow. However, concerns regarding inadequate infrastructure (43.5 %) and privacy issues (37.1 %) were prevalent. Significant associations were found between AI knowledge and location, self-perception, and willingness to train (p < 0.001).

Conclusions

The study highlights critical knowledge gaps in AI among Nigerian nursing students despite a high willingness for adoption. AI education should be integrated into nursing curricula, and infrastructure improvements are necessary to support AI implementation in healthcare. Addressing these gaps will better prepare nursing students for the evolving landscape of AI-driven healthcare.

Item Type:	Article
Status:	Published
DOI:	10.1016/j.nepr.2025.104511
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/12513

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