This study investigates "The Role of AI in Management" and aims to understand the impact of AI technologies on various management practices within organizations. The problem of the study arises from the increasing adoption of AI in the business world and the need to comprehend its implications for managerial decision-making, organizational efficiency, and employee experiences. The study focuses on both theoretical and practical aspects, providing insights that can inform academic research and guide organizations in leveraging AI effectively. To address the research problem, a cross-sectional study design using a questionnaire as the primary data collection tool has been selected. This design allows for the collection of quantitative data at a specific point in time, providing a snapshot of the relationship between AI and management practices. The questionnaire will be administered to professionals and managers across diverse industries, representing organizations that have implemented AI technologies in their management processes. The importance of this study lies in its theoretical and practical contributions. Theoretically, it expands the understanding of the role of AI in management by examining its impact on decision-making processes, organizational structures, and employee roles. It contributes to the existing body of knowledge by exploring the nuances and complexities of AI implementation in managerial contexts. Practically, the findings will provide insights and recommendations for organizations seeking to adopt or optimize AI technologies in their management practices. It will guide decision-makers in understanding the potential benefits, challenges, and best practices associated with AI integration. The scope of this study encompasses professionals and managers across various industries, ensuring a diverse representation of AI adoption in management practices. The focus is on organizations that have implemented AI technologies and are actively utilizing them in their decision-making processes, resource allocation, and performance evaluation. The study aims to capture the perceptions, experiences, and attitudes of participants related to the role of AI in management. Data will be collected through a structured questionnaire distributed electronically to the selected participants. The questionnaire will capture quantitative data on participants’ perceptions, experiences, and attitudes towards AI in management. It will include closed-ended and Likert-scale questions, enabling efficient data collection and analysis. The collected data will be analyzed using appropriate statistical techniques, including descriptive statistics, correlation analysis, and regression analysis. By employing this methodology and research tools, this study seeks to provide a comprehensive understanding of the impact of AI on management practices. The findings will contribute to both theoretical knowledge and practical insights, guiding organizations in leveraging AI effectively to enhance decision-making, improve operational efficiency, and foster innovation in management processes.
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