A Comparative Study of AI Tools Adoption and Its Impact on Educational Practices in Public and Private Universities

Abstract

Artificial Intelligence (AI) is increasingly becoming and integral component of the future of higher education, that is transforming traditional approaches to teaching and learning, academic research, assessment practices, and institutional administration. The literature of empirical studies covering emergent and resource-constrained situations is scarce although the scope of its influence has been rapidly expanding on the international stage. As a result, this paper involves the comparative analysis of the use of AI tools and the perceived effect of the latter on both the public and the private universities in the Khyber Pakhtunkhwa (KP) province of Pakistan. The study assumes that adoption depends on the perceived usefulness, perceived ease of use, institutional compatibility, and structural support thus analyzing the hypothesis that adoption is the nexus between technological integration and salient educational outcomes. Using quantitative, comparative survey as the research methodology, data were gathered involving 460 respondents, including faculty members and postgraduate students who were recruited, in a distributive way, in a public university (Gomal University), and a non-governmental university (Qurtuba University) in the city of Dera Ismail Khan. The instrument that was rigorously validated measured five central dimensions namely the rate of adoption of the AI tool, perceived effectiveness, user satisfaction, perceived performance improvement, and motivation. To question disparities in sectors, descriptive statistics have been employed along with independent-sample t-tests. The empirical study demonstrates a significantly greater rate of AI-tool use in the case of the public university, compared to the one in the private one. However, the two institutions did not show any statistically significant difference as regards to perceived effectiveness, user satisfaction, performance, or motivational outcomes. These results indicate that, despite the role of institutional context in access, the delivery of infrastructure, and the adoption patterns, the perceived pedagogical importance of AI technologies overlaps in sectors when the process of meaningful integration becomes a reality. That is, the adoption gap seems to be organized, but not observational of the difference of education levels. The study advances the academic discourse on the adoption of artificial intelligence (AI) in higher education, and especially in developing countries, by explaining how institutional preparedness, digital infrastructure, transparency in governance, and capacity development in the professional sphere can play a central role in supporting sustainable adoption of AI. The results highlight the need to establish institutional policies, sound ethical frameworks, and policy interventions that are narrowly focused and with which together would help to make AI technologies in KP and similar emerging environments the subject matter of responsible, fair, and pedagogically significant integration.