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Drafting a Digital Transformation Strategy for Project Management Sector – Empirical Study on Uae

„Аз-буки“ от „Аз-буки“
30-12-2023
in Uncategorized
A A

Mounir el Khatib, Shikha al Ali,
Ibrahim Alharam, Ali Alhajeri
School of Business & Quality Management,
Hamdan Bin Mohammed Smart University – Dubai, UAE
Dr. Gabriela Peneva, Assist. Prof., Prof. Jordanka Angelova,
Mahmoud Shanaa
Technical University of Sofia

https://doi.org/10.53656/str2023-6s-3-dra

Abstract. It is without a doubt that the impact of digital transformation and disruptive technologies has impacted all industries globally. There is hardly any sector that is left untouched by this form of innovation. This is also true for the power sector, which is the industry targeted for this study. The power sector is crucial for human existence, and hence, it is the use of different kinds of technology that must be employed at the helm of its operations. These different kinds of technology are related to AI, Robotics, IoT, and Big Data. The major intention behind these technologies should be to pace up different projects managed in the industry. Therefore, the company selected for this project is Dubai Electricity and Water Authority (DEWA). It is a company that is involved with various technological projects ranging from smart grids to digital meters to managing customer data. By interviewing thirteen key people from the company, the study highlights the current status of technology and how it is being employed by different power sector companies. In the end, it has been deduced that the future of the power industry relies on its adaption of green energy generation, and hence, all the efforts of the companies should be directed toward producing green energy with the help of modern technology. Also, it was found that the use of AI can enhance the efficiency of the projects, making them less risky. Therefore, the use of AI ensures that the projects are less prone to risks and have a higher chance of success..
Keywords: project management; digital transformation; digital disruption; disruptive technologies; machine learning; artificial intelligence

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