Abstract

Higher education admissions in the UAE has long been treated as an administrative process rather than a strategic one. Students are selected on the basis of past academic performance, and qualifications are conferred with limited reference to future national needs. Meanwhile, the national ambitions set out in Centennial 2071 and AI Strategy 2031 require something entirely different: a generation of graduates capable of driving a knowledge economy that barely existed when those students first sat their school exams. This thesis argues that AI-driven admissions, currently deployed mainly for speed and efficiency, can and should be redesigned to do something much more purposeful. By integrating strategic foresight methodologies into how UAE institutions select students, admissions can become a genuine instrument of national workforce development rather than a digital version of what admissions offices have always done. The research draws on a qualitative secondary-data approach, applying four foresight tools in sequence: PESTEL analysis to map the macro-environmental forces shaping UAE AI admissions; Causal Layered Analysis to dig beneath the surface and identify the cultural assumptions and deep narratives that make change difficult; scenario planning to construct four plausible futures for 2031; and backcasting to work backwards from the preferred future and identify what needs to happen now. The findings are clear on one point that the literature tends to avoid: the biggest barriers to transformation are not technical. They are cultural. The belief that past academic performance reliably predicts future contribution, and the idea that admissions is about sorting rather than shaping, are embedded deeply enough that policy alone will not shift them. The thesis concludes with an integrated strategic framework and a phased implementation roadmap, along with recommendations for the UAE Ministry of Education, the Commission for Academic Accreditation, and institutional leadership at UAEU, AUS, Zayed University, HCT, and RIT Dubai.

Publication Date

8-2026

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Woody Wade

Comments

This thesis has been embargoed. The full-text will be available on or around 7/10/2027.

Campus

RIT Dubai

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