USING APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN QATAR'S BROKERAGE FIRMS: OPPORTUNITIES AND CHALLENGES

Abstract

Artificial Intelligence is becoming popular among organizations operating within financial and non-financial sectors. It is utilized in managing several aspects of organizational functions, including planning, controlling, and decision-making. More specifically, AI is under-explored in managing investment, such as predictions and decision-making. The first motivation was the limited research on AI adoption at the micro-level. Further motivation stemmed from the little research on AI adoption that explored the dynamic capabilities of acquiring AI-based systems in driving engines for a rapidly changing environment. This motivated the present thesis to explore the conditions and processes behind adopting AI solutions in QBFs. This thesis investigates the organizational capabilities of Qatari brokerage firms ("QBFs") in responding to AI technology in rationalizing investment decisions. This responsiveness was examined by observing and measuring the level of the three Dynamic Capabilities of organizations (Sensing, Seizing, and Reconfiguring) among these companies, along with specifying the enablers and disablers and using a qualitative approach and corresponding methods (16 semi-structured interviews with decision-makers in the financial services realm). The findings indicate that QBFs experience a high level of sensing capacities through the ability to rapidly detect opportunities and threats amid fierce competition and environmental changes, allowing them to understand customers better and develop predictive analytics. However, it was found that a moderate level of seizing capacities through integrating AI into processes led by professionals, drawing new insights from information (understanding patterns), and moving towards more efficient data-driven decision-making. Consequentially, QBFs suffered a weak level of transformation capacities through supporting asset optimization following the changes in context and ensuring the right level of investments in infrastructure and maintenance. This thesis dealt with the topic of dynamic capabilities, which is one of the recent topics in the strategic management of organizations. Despite the interest in this topic, financial services companies have not received sufficient attention regarding their dynamic capabilities, especially concerning incorporating AI technology in their operations and business models. Therefore, the study attempts to discover the extent of dynamic capabilities at Qatar Brokerage Firms ("QBFs") in adopting AI technology, which is of great significance to enhancing competitiveness in the market. Accordingly, this thesis contributes to the dynamic capabilities theory by providing a qualitative study on requirements, synthesis, procurement, and incorporation of external performance enhancers considering various stages of dynamic organizational capabilities. From a practical point of view, the thesis helps direct and guide senior management of QBFs to the areas of importance in improving the performance of their organizations and guaranteeing their competitiveness and sustainability.