Abstract:

Artificial intelligence (AI) is reshaping higher education through new forms of learning support, personalization, and pedagogical innovation. However, these benefits may coexist with unequal conditions for meaningful digital participation. This study examines the relationships among perceived AI use, learning personalization, pedagogical innovation, educational inclusion, digital inequality, and perceived equity among undergraduate students at a private university in Lima, Peru. A quantitative, non-experimental, cross-sectional design with an explanatory and predictive orientation was adopted. Data were collected from 312 students through a structured questionnaire and analyzed using partial least squares structural equation modeling (PLS-SEM). The measurement model demonstrated adequate reliability, convergent validity, and discriminant validity. Perceived AI use was positively associated with learning personalization (β = 0.62, p < 0.001) and pedagogical innovation (β = 0.55, p < 0.001), while personalization was positively associated with educational inclusion (β = 0.47, p < 0.001). Digital inequality was negatively associated with perceived equity (β = −0.39, p < 0.001). The findings reveal an asymmetric socio-technical pattern: perceived pedagogical value can expand without automatically eliminating equity-related constraints. The study contributes evidence from an underrepresented Latin American setting and highlights the need for higher education institutions to manage AI adoption not only as a source of pedagogical innovation but also as an institutional capability requiring equitable digital participation.