| Abstract [eng] |
This thesis examines the application of algorithmic decision-making (ADM) in accounting information systems (AIS). While artificial intelligence (AI) and its use in the financial sector receive considerable attention in contemporary literature, the specific integration of ADM into AIS is a relatively underexplored area. This study aims to bridge the existing knowledge gap by analyzing how ADM can be used for more efficient, accurate, and faster processing of financial data and decision-making processes. The object of the study: algorithmic decision-making within the context of accounting information systems. The aim of the research: to investigate the application of algorithmic decision-making in accounting information systems. A review of scientific literature revealed various areas of innovation implementation, advantages, challenges, and other trends that could influence the integration of ADM into AIS. Based on this analysis, a conceptual model was developed, describing the key factors, advantages, and challenges influencing the integration of ADM into AIS. To verify this theoretical structure, an empirical qualitative study was conducted. The thesis thoroughly examines how ADM technologies are implemented in practice, particularly in the banking sector, where there is a necessity to process vast amounts of data quickly while ensuring high security and accuracy standards. The study involved a detailed analysis of ADM systems in five different banks, discussing each bank's experiences and challenges related to the integration and use of these systems. The analysis showed that ADM provides several advantages, including process automation, error reduction, and faster response to changing market conditions. However, the study also revealed challenges such as data privacy, system maintenance, and staff training. These challenges require comprehensive organizational and technical strategies to ensure smooth and ethical application of ADM. The thesis concludes that ADM technologies hold significant potential in AIS, but careful monitoring and refinement of their implementation are necessary to avoid potential ethical and operational risks. Further research is recommended, particularly analyzing the long-term impact of ADM application and user experiences, as well as developing guidelines on how best to integrate and use these technologies in different business environments. |
