Integration of artificial intelligence in nursing education: a cross-national exploration

Abstract

BACKGROUND: Understanding nurse educators' perceptions of Artificial Intelligence (AI) in education, particularly cross-nationally and considering cultural and exposure influences, remains limited. This study addressed this gap by determining the impact of AI integration in nursing education. METHODS: Participants included 1021 nurse educators from the Philippines, Saudi Arabia, India, and Egypt, with data collected between January and March 2025. RESULTS: Perceived benefits of AI showed consistent means across countries, though significant differences (p < 0.001) were observed in perceived threats, exposure, and the influence of culture by country. Strong positive correlations emerged between exposure to AI and both trust in AI (r = 0.653) and perceived benefits (r = 0.625). Nationality significantly predicted perceived risks, exposure, and cultural impact (all p < 0.001), emphasizing the relevance of cultural background to AI applicability. CONCLUSION: Nurse educators acknowledge AI's educational potential but show diverse perceptions regarding risks, exposure, and cultural impact. Increased AI exposure fosters trust and perceived benefits, highlighting the need for contextualized, culturally-attuned, and exposure-driven AI integration in nursing education.

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