Analysis of the Strategy for Improving the Efficiency of Business Processes through Artificial Intelligence

Master's thesis focuses on a comprehensive analysis of strategies to enhance the efficiency of business processes using artificial intelligence (AI). In the context of the continually evolving field of AI in business practice, the aim of the thesis is to identify key challenges and benefits of this technology and propose approaches that could be successfully implemented in the corporate environment. The thesis systematically examines the latest insights and trends in the field of AI and business processes, with a focus on factors influencing the success of implementation. With an analysis of professional literature, it addresses issues such as the novelty of the topic, relative lack of relevant data, dynamics of AI development, and the technological environment in which companies operate. The methodology includes a combination of logical methods, including induction, deduction, and abduction, with an emphasis on logical abductive analysis in the theoretical part. The practical part of the thesis relies on content analysis of available information on the implementation of AI in business processes at selected companies, evaluating the extent to which strategies differ and where common elements are identifiable. The conclusions of the thesis highlight the variability in companies' approaches to AI implementation, with a key element being the ability to leverage available data. The proposed strategies are formulated with consideration for this variability and emphasize the importance of continuous training and involvement of the human element in assessing AI outputs. The findings have practical implications for companies considering the deployment of AI to optimize their processes, providing a beneficial approach to adapting to a rapidly changing technological environment.