This doctoral research proposal explores how AI-assisted decision-making can support quality improvement in higher education and professional training organizations in Kuwait and the United Arab Emirates. The study focuses on the use of AI to measure, monitor and analyze quality-related information and to support decisions related to competency assurance, training effectiveness, assessment and learning quality, and continuous improvement. The study also examines the role of transformational leadership and human judgement in the effective, responsible and context-sensitive use of AI-generated information. Human judgement is considered essential for interpreting, validating and challenging AI-generated information and for translating it into appropriate quality-related decisions. Transformational leadership is examined as an organizational context that supports learning, responsible change and continuous improvement. The research adopts a pragmatist philosophy and an exploratory sequential mixed-methods design, with a qualitative-dominant approach. Semi-structured interviews will be used to explore stakeholder experiences and perceptions, followed by a questionnaire developed from the qualitative findings. The study aims to develop a context-sensitive framework and practical recommendations for using AI-assisted decision-making to support quality improvement in higher education and professional training organizations in Kuwait and the United Arab Emirates.
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RANIA KANANA (2026) studied this question.
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