When AI Divides: Faculty Experiences of AI-Related Disadvantage and Digital Stratification in Pakistani Higher Education through Conservation of Resources and Social Comparison Perspectives

Purpose This study explores how full-time faculty members in Pakistani higher education institutions who experience AI-related disadvantage describe its psychological and professional impacts, how they recall responding to it over time, and how experiences vary across institutional and demographic contexts, with attention to the unequal distribution of technological, informational and relational resources. Design/Methodology The study used an interpretivist, phenomenologically oriented qualitative approach, gathering data through in-depth semi-structured interviews with 30 full-time faculty members from public and private universities who reported experiencing AI-related disadvantage (recruited through snowball sampling). The interviews were recorded, transcribed and analysed through inductive-led thematic analysis in NVivo 14, with theory-informed interpretation drawing on Conservation of Resources and Social Comparison theories. Findings Participants described AI-related disadvantage as bringing psychological strain (performance anxiety, perceived inferiority and identity disruption) and structural-professional exclusion, particularly from AI-enabled collaboration networks and AI-related decision-making. After initially negative reactions, many participants retrospectively described adaptive up-skilling, whereas perceived sustained disadvantage was associated with self-reported withdrawal, reduced motivation and turnover intentions. Responses varied with institutional support, peer inclusion, sector and academic rank. Findings are based on retrospective self-reports from a purposive sample of disadvantaged faculty and are not statistically generalisable. Research Implications The findings offer practical implications for university administration by highlighting the need to foster inclusive and equitable digital environments through policies that ensure fair access to AI tools and training, promote transparent information sharing and strengthen formal and informal academic collaboration, in order to mitigate digital inequality and exclusion. Originality The study extends research on digital inequality by offering a qualitative, context-specific account of how faculty in Pakistani higher education experience AI-related disadvantage as a resource gap with psychological and relational consequences, integrating Conservation of Resources and Social Comparison perspectives (a conceptual contribution emerging from participants’ accounts, not a proven causal mechanism). It offers tentative recommendations for more equitable digital transformation in universities.