Abstract

This thesis investigates how Artificial Intelligence (AI) can be used to improve operational efficiency, profitability, and customer satisfaction in the UAE real estate market with a specific case study of Al Zaeem Commercial Brokers. The study intends to assess the change that AI technologies are bringing to the industry, specifically in property valuation, customer relationship management, and operational processes. The research gives a detailed discussion of how AI tools, including machine learning, automated valuation models, and predictive analytics, have been integrated in streamlining the real estate processes and enhancing decision-making.

In this study, the author uses a focused case study of Al Zaeem Commercial Brokers to identify the issues as well the opportunities of using AI in an established industry. The results show that AI not only leads to increased efficiency but also brings to the company considerable financial benefits, such as reduced costs, increased revenues, and better return on investments (ROI) to real estate companies. In the paper, the authors also determine the main barriers to the application of AI, including high implementation costs, workforce adjustment, and regulatory issues that should be overcome in order to be successfully integrated.

This thesis will add to the expanding literature on the effects of AI on the real estate sector in the Gulf region by investigating how AI is applied in the UAE real estate market. It offers a rich insight to scholars and professionals who want to know how AI can be used to drive innovation, streamline operations, and enhance the overall business performance of real estates. The study also adds to the theory of the adaptation of AI in the new markets, and provides a suggestion on the way to improve AI-based strategies in the changing real estate of the UAE.