The accelerating diffusion of Artificial Intelligence (AI) is profoundly reshaping organizational practices, competitive dynamics, and sustainability trajectories across global business ecosystems. In innovation-oriented contexts such as Dubai and the United Arab Emirates (UAE), AI adoption is further amplified by strong governmental support and national strategic visions. This study explores the adoption, perceived benefits, and emerging risks associated with AI through six in-depth qualitative interviews with external advisory professionals operating in the UAE consulting sector. The findings reveal that AI functions as a strategic equalizer, enabling efficiency, scalability, and service quality improvements, especially for startups and small-to-medium enterprises (SMEs). At the same time, the study highlights critical challenges related to data governance, environmental sustainability, over-reliance on AI outputs, hidden economic costs, and uneven governance structures. By offering context-specific insights from a rapidly developing innovation hub, this paper contributes to the literature on responsible AI adoption and provides actionable guidance for managers navigating AI-driven transformation.
Strategic Adoption of AI in Dubai: Preliminary results from an Advisory-Centered Perspective
Rossi, Marco Valerio;
2026-01-01
Abstract
The accelerating diffusion of Artificial Intelligence (AI) is profoundly reshaping organizational practices, competitive dynamics, and sustainability trajectories across global business ecosystems. In innovation-oriented contexts such as Dubai and the United Arab Emirates (UAE), AI adoption is further amplified by strong governmental support and national strategic visions. This study explores the adoption, perceived benefits, and emerging risks associated with AI through six in-depth qualitative interviews with external advisory professionals operating in the UAE consulting sector. The findings reveal that AI functions as a strategic equalizer, enabling efficiency, scalability, and service quality improvements, especially for startups and small-to-medium enterprises (SMEs). At the same time, the study highlights critical challenges related to data governance, environmental sustainability, over-reliance on AI outputs, hidden economic costs, and uneven governance structures. By offering context-specific insights from a rapidly developing innovation hub, this paper contributes to the literature on responsible AI adoption and provides actionable guidance for managers navigating AI-driven transformation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

