| Abstract [eng] |
83 pages, 12 tables, 18 figures, 90 references, Lithuanian language. Due to recent technological advancements, the auditing and accounting professions have undergone significant changes. These transformations have led to the emergence of new services for clients, such as financial analysis and consulting. In addition, the accounting and auditing professions have witnessed the growth of new types of services and activities. It is essential for accounting professionals to understand the impact of artificial intelligence on their field. Although artificial intelligence technologies have reduced the use of traditional accounting practices, they have also increased the transformation of accountants’ and auditors’ roles. Therefore, it is relevant to investigate the impact of artificial intelligence on accounting and auditing. The object of this master’s thesis is artificial intelligence solutions in accounting and auditing. The aim of the thesis is to determine the benefits of applying artificial intelligence solutions in accounting and auditing. To achieve this aim, the following objectives were set: to reveal the concept of artificial intelligence and the current state of its application in accounting and auditing based on scientific literature; to analyze artificial intelligence tools and platforms already applied in accounting and auditing, as well as their advantages and disadvantages; to develop a research methodology for investigating the opportunities for the development of artificial intelligence in accounting and auditing; and to conduct a study on the opportunities for the development of artificial intelligence in accounting and auditing. The methods used in the thesis include scientific literature analysis, systematization, generalization, a qualitative semi-structured interview method, and a quantitative questionnaire survey method. Artificial intelligence is bringing substantial changes to accounting and auditing. The application of artificial intelligence technologies significantly increases work efficiency, accuracy, and big data analytics capabilities. Although the benefits of these technologies are undeniable, their 80 successful implementation is mainly hindered by the lack of specialists capable of combining financial knowledge with technological skills, as well as by high implementation costs. Furthermore, in order to avoid data security breaches and the loss of analytical skills, it is necessary to ensure that responsibility and final decision-making control remain in human hands. Therefore, future prospects in this field will depend not only on the advancement of algorithms themselves, but also on organizations’ ability to invest in employee qualification improvement and the establishment of clear legal regulation. |
