M15 - IT ManagementReturn

The paper deals with the possibilities of using artificial intelligence in tasks and activities of management accounting. Its aim is to create a comprehensive overview of the current state and possibilities of utilization of artificial intelligence technologies in management accounting, based on a systematic literature review of empirical literature. Academic articles were complemented by current surveys of research consulting companies and professional organizations and bodies. Literature review results are grouped by specific key areas of management accounting, analyzing the tools for facilitating the budgeting and calculation processes or performance measurement. Artificial intelligence is also presented as a customization process or strategic decisions support. Resulting from the executed analysis, a few fundamental aspects affecting the success of artificial intelligence technologies implementation were determined, primarily the quality of the primary data and reasonable choice of activities suitable for automation.

The article outlines the risks associated with the implementation of the new information system in the company. The core of the article is the analysis of risk factors in the various phases of ERP system life from the point of view of accounting and its basic functions, ensuring a fair and true view of accounting in the financial statements. Analysis has been made based on secondary date and its application to the accounting needs. Many implementations end with exceeded budget, time schedule or both. Main risks are identified in the chapter 3. From the perspective of accounting, the riskiest phases are system selection, implementation and production system, and the bottlenecks are migration of transaction and master data, decision on setting the correct date for transition to the new system, and ensuring the balance sheet continuity of accounting books in both systems. Accounting risks are also relating to non-compliance with the tax obligations and penalties and fines resulting therefrom. Minimizing these risks helps identify key success factors for each phase.