From AI Use to Responsible AI Preparedness: Professional Learning Needs in Ukrainian Higher Education

Abstract

The rapid integration of artificial intelligence into higher education has increased the need to distinguish routine AI use from preparedness to use this technology responsibly and ethically. The study examines responsible AI preparedness as a dimension of continuous digital professional learning in Ukrainian higher education by analysing differences in perceived ethical AI learning needs across career stages and levels of AI use and their association with institutional AI-policy environments. Cross-sectional survey data from 2,004 respondents representing Ukrainian higher education institutions were analysed using descriptive statistics, chi-squared tests, Cramér’s V, cumulative-link ordinal logistic regression, interaction models, adjusted predicted probabilities, and binary logistic regression. AI use was widespread: 74.0% used AI at least periodically, while 33.1% reported high ethical AI learning needs and 42.2% substantial gaps in institutional rules or guidance. Among active AI users, 472 respondents were classified as active but underprepared, representing 31.8% of active users and 23.6% of the HEI sample. In the binary logistic model restricted to active users, reporting no institutional AI policy was associated with 47.3% higher odds of high ethical learning need (OR = 1.47, 95% CI [1.11, 1.95]), while policy uncertainty was associated with 64.2% higher odds (OR = 1.64, 95% CI [1.26, 2.14]). In the cumulative-link ordinal model for the full HEI sample, ethical learning needs were higher among respondents aged 50–59 (OR = 1.64) and 60–69 (OR = 1.86) than among those aged 18–29. Research experience significantly moderated the association between AI-use intensity and perceived learning need (LR χ²(3) = 8.82, p = 0.032). The findings support targeted professional learning.