Journal of Advances in Artificial Intelligence and Machine Learning

Journal of Advances in Artificial Intelligence and Machine Learning

Open Access
ISSN: 3069-8316
Review Article

Digital Transformation Strategies for UAE Startups in the AI Era: A Critical Literature Review and Qualitative Research Framework

Authors: Shankar Subramanian Iyer, Brinitha Raji, Rajesh Arora, Raman Subramanian.

DOI: 10.33425/3069-8316.1013


Abstract

This article presents a comprehensive examination of digital transformation strategies for UAE startups navigating the artificial intelligence era, synthesizing insights from 163 scholarly sources and proposing a qualitative research framework based on 15 senior leadership interviews. The critical literature review reveals that successful digital transformation in UAE startups requires the strategic integration of three interdependent pillars: digital leadership capabilities, AI adoption practices, and organizational readiness. Key findings indicate that UAE startups face distinct challenges including skills shortages, ethical governance concerns, and resource constraints, while benefiting from supportive government initiatives aligned with national smart transformation agendas. The proposed qualitative methodology employs semi-structured interviews with 15 senior leaders across UAE startup ecosystems to capture nuanced insights into strategic decision-making, implementation challenges, and success factors. This research contributes to both academic understanding and practical guidance for startup leaders, policymakers, and ecosystem stakeholders seeking to accelerate digital transformation in the UAE's dynamic entrepreneurial landscape.

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Citation: Shankar Subramanian Iyer, Brinitha Raji, Rajesh Arora, et al. Digital Transformation Strategies for UAE Startups in the AI Era: A Critical Literature Review and Qualitative Research Framework. J Adv Artif Intell Mach Learn. 2026; 2(1). DOI: 10.33425/3069-8316.1013
Editor-in-Chief
Jose Luis Verdegay Galdeano
Jose Luis Verdegay Galdeano
Department of Computer Science and Artificial Intelligence | University of Granada

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Impact Factor 2.4*
Acceptance Rate 75%
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