AI Adoption in Higher Education: A Comparative Study of Institutional Readiness and Challenges

Abstract

This study explored the patterns of AI adoption, varying degrees of institutional readiness, and challenges of implementation in higher education in Pakistan, employing a mixed-methods comparative approach. To collect relevant data, the researchers used structured questionnaires from 250 faculty members and administrators and conducted semi-structured interviews with 30 key stakeholders in 5 sampled universities, including public, private, and federally chartered institutions. The results indicated stark differences in the level of AI readiness from different institution types; specifically, private universities showed more advanced infrastructural capability (3.8/5.0), as opposed to public (2.9) and federal institutions (3.2). Notably, while 72% of respondents reported a general awareness of AI, only 22% of institutions were reported to have AI applications, which were primarily operated as pilots and not fully integrated into the institution. The predominant barrier to implementation was identified as a lack of financial resources (82%), followed by insufficient infrastructure (78%), and a lack of technical expertise (74%). From the qualitative assessment, five thematic challenges of implementation emerged: gaps in leadership vision, deficits in technical capacity, faculty resistance to change, financial sustainability concerns, and absence of policy frameworks. Additionally, the lack of comprehensive change management was evident, as 64% of respondents expressed concerns about job security and 72% about data privacy. These findings suggest the need for phased approaches, along with substantial infrastructural investments, training, and clear policy frameworks to address the AI adoption imbalance in higher education institutions in Pakistan.