Continuous improvement in the age of AI: human and relational barriers in public higher education

Purpose This study investigates the human and relational dynamics of artificial intelligence (AI) adoption for continuous improvement in public higher education institutions (HEIs). It explores how AI integration affects employees' basic psychological needs – autonomy, competence, and relatedness – within the public sector's value-driven context. Design/methodology/approach The research employs a mixed-methods embedded design. Primary data consists of 330 semi-structured interviews with administrative staff across six Italian universities. Qualitative thematic analysis is integrated with Chi-square (χ2) statistical tests to identify significant associations between employees' perceptions and socio-demographic factors, and macro-institutional profiles based on organizational digital maturity. Findings The results reveal a paradox of automation: AI is welcomed as a tool for operational autonomy when it emancipates staff from repetitive tasks but is rejected when it threatens decisional sovereignty or ethical accountability. While AI can augment competence for digitally literate staff, it risks cognitive atrophy and workplace sterilization. Relatedness emerges as a non-negotiable pillar, with staff universally resisting AI applications that substitute human interaction for student support. Originality/value The study shifts the focus from technological performance to micro-foundational motivational mechanisms by applying Self-Determination Theory (SDT) to AI adoption in the public sector. It contributes a new conceptual framework that identifies a legitimacy threshold, distinguishing between AI as an assistive infrastructure versus a professional substitute.