Thesis Abstract

Abstract
Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize various aspects of business operations, particularly in decision-making processes. This thesis aims to analyze the impact of AI on business decision-making processes and explore the implications for organizational performance and strategic outcomes. The study will investigate how AI technologies, such as machine learning algorithms, natural language processing, and cognitive computing, are being integrated into decision-making frameworks across different industries. The research will begin with a comprehensive literature review to examine the theoretical foundations and previous studies related to AI in business decision-making. This review will highlight the benefits and challenges associated with AI adoption in decision-making processes, as well as the factors influencing successful implementation. By synthesizing existing knowledge, the study will identify gaps in the literature and propose a conceptual framework for understanding the impact of AI on business decision-making. In the methodology chapter, a mixed-methods approach will be employed to collect and analyze data from both qualitative and quantitative sources. Surveys, interviews, and case studies will be conducted to gather insights from business leaders, AI experts, and decision-makers in various organizations. The data will be analyzed using statistical techniques and thematic analysis to identify patterns, trends, and key themes related to AI adoption and its impact on decision-making processes. The findings chapter will present the results of the data analysis, providing empirical evidence on the effectiveness of AI in enhancing decision-making efficiency, accuracy, and strategic alignment. The discussion will explore the implications of these findings for businesses seeking to leverage AI technologies for competitive advantage and organizational growth. Key factors influencing the successful implementation of AI in decision-making will be identified, along with recommendations for practitioners and policymakers. In conclusion, this thesis will contribute to the growing body of research on the impact of AI on business decision-making processes. By examining real-world cases and expert perspectives, the study will provide valuable insights into the opportunities and challenges of integrating AI technologies into organizational decision-making frameworks. The findings will offer practical guidance for businesses looking to harness the power of AI for improved decision-making and sustainable competitive advantage. Keywords Artificial Intelligence, Business Decision-Making, Machine Learning, Organizational Performance, Strategic Outcomes, Technology Adoption

Thesis Overview