EMPLOYING ARTIFICIAL INTELLIGENCE APPLICATIONS IN PROGRAM ACCREDITATION PROCEDURES AT SAUDI UNIVERSITIES: A MIXED-METHODS STUDY

Abstract

The present study aimed to explore the reality of employing Artificial Intelligence (AI) applications in program accreditation procedures at Saudi universities, while identifying the most prominent challenges and proposals for enhancing such integration. The study adopted a mixed-methods research design for data collection and analysis; a questionnaire was utilized to gather quantitative data from members of development and quality committees, followed by a qualitative phase involving semi-structured interviews to interpret the extreme quantitative results.

The findings revealed that the reality of AI employment across all program accreditation domains—including Policy and Governance, Key Performance Indicators (KPIs), Continuous Improvement, Stakeholder Engagement, and Post-Accreditation Follow-up—was rated at a "Low" degree overall. Furthermore, the qualitative results indicated a significant gap between the available technical potential and both institutional and human readiness. The study concluded by presenting a set of recommendations, most notably the necessity of drafting clear policies for AI governance, developing digital infrastructure, and training faculty members to employ smart tools in quality processes in a sustainable manner.