Background <p>The rapid development of artificial intelligence (AI) is reshaping healthcare delivery and nursing practice. However, nurses’ acceptance of AI varies considerably. Identifying distinct patterns of AI acceptance and their associated characteristics may help inform tailored strategies for the integration of AI technologies into nursing practice.</p> Methods <p>Between November and December 2025, a total of 595 nurses were recruited using a convenience sampling method. Data were collected using a general demographic questionnaire and the Artificial Intelligence Attitude at Work (AAAW) scale. Latent profile analysis was conducted to identify distinct subgroups of nurses based on their AI attitude patterns. Univariate analyses and multinomial logistic regression were used to explore factors associated with profile membership.</p> Results <p>Three latent profiles of AI attitudes were identified: Low AI Acceptance–Cautious Observational Profile (25.7%), Moderate AI Acceptance–Rational Evaluative Profile (31.8%), and High AI Acceptance–Utility-Oriented Profile (42.5%). Multinomial logistic regression analysis revealed that sex, age, educational level, professional title, nursing hierarchy level, and hospital level were significantly associated with profile membership. Female nurses, those with higher educational attainment, intermediate professional titles, lower nursing hierarchy levels, and those working in tertiary hospitals were more likely to belong to the high AI acceptance profile, whereas nurses aged ≥ 40 years were less likely to be classified into this profile.</p> Conclusions <p>Nurses’ attitudes toward artificial intelligence are heterogeneous and can be categorized into distinct latent profiles.Individual characteristics, professional roles, and organizational context were associated with AI acceptance profiles among nurses.</p> Trial registration <p>Not applicable.</p>