The Gap Between Artificial Intelligence Adoption and University Performance: The Role of Smart Steering and Digital Governance

Abstract

Research on artificial intelligence in higher education has mainly examined teaching and learning applications, whereas its integration into management control, institutional steering and digital governance remains insufficiently documented. This study investigates the relationships between AI adoption, smart steering, digital governance and perceived university performance, with particular attention to the gap between technological appropriation and institutional outcomes. A cross-sectional quantitative survey was conducted among 80 university stakeholders. Four five-item constructs measured on Likert scales were analysed using Cronbach's alpha, Pearson correlations, multiple regression, bootstrap mediation and comparisons across AI-use groups. The scales showed strong reliability (alpha from 0.865 to 0.953). AI adoption was strongly associated with smart steering (r = 0.691, p < 0.001) and moderately associated with digital governance (r = 0.408, p < 0.001). However, the performance model was not significant (R² = 0.063, F = 1.709, p = 0.172) and had a small effect size (f² = 0.067). Indirect effects were not supported, although regular users reported higher adoption and smart-steering scores. The findings reveal an appropriation gap: AI initially reshapes information routines and steering practices without immediately producing measurable institutional gains. Universities should therefore prioritise data quality, staff capabilities, integration into dashboards and decision routines, and proportionate governance mechanisms. Performance should subsequently be assessed through objective indicators defined before deployment, rather than inferred from usage levels alone. The study provides a transparent exploratory baseline and does not establish causal relationships across institutions or over time empirically here.

JEL Classification: I23; M10; M15; O33.

Paper type: Empirical exploratory research.