| Abstract [eng] |
The main purpose of this master's thesis is to determine the possibilities of applying and utilising ML, DL, NLP and IPA technologies in the field of accounting. The work consists of two main parts the analysis of scientific literature and an empirical study, along with conclusions and recommendations. The first part systematically examines existing ML, DL, NLP and IPA solutions, investigates shifts in employee roles and professional competencies, assesses organisational readiness for technological transformation and change management and analyses the constituent elements of the TOE framework. Following the literature review a TOE-TPS-ISS conceptual model was constructed to serve as the theoretical foundation for the empirical investigation. Based on the proposed conceptual model, a mixed-methods study was conducted. The qualitative component involved semi-structured interviews with four domain experts from accounting firms or departments, who provided practical insights into AI adoption, its organisational benefits and the challenges encountered during implementation. The quantitative component comprised with the aim of establishing the prevalence and scope of ML, DL, NLP and IPA utilisation in accounting practices. The collected data were analysed using thematic and descriptive statistic methods. The findings of the qualitative study indicate that the integration of AI solutions in accounting significantly enhances process efficiency, facilitates the automation of routine tasks, reduces the incidence of errors and improves the quality of data analysis. Contemporary accounting professionals are required to demonstrate critical thinking, creativity, analytical competence and the capacity to provide strategic client advisory services. The quantitative study revealed a statistically significant negative correlation between the perceived benefits of AI and the emphasis places on implementation challenges (r = -0.32, p < 0.001), suggesting that organisations with a strong understanding of AI value are less deterred by adoption barriers. The results further indicate that micro, macro and medium-sized enterprises most frequently employ generative AI tools, automated invoice and receipt recognition systems and document integration solutions. Sustained management support, structured employee training programmes and transparent organisational communication were identified as critical success factors in the technology adoption process. In the conclusions and recommendations, the principal findings are synthesised, leading to the overarching conclusions that AI solutions are assuming an increasingly pivotal role in accounting and are fundamentally reshaping the profession. It is recommended that organisations direct greater effort toward developing employee competencies, ensuring responsible AI development and maintaining compliance with the EU AI Act and the GDPR regulations. The findings of this study may serve as a valuable reference for accounting firms contemplating the adoption of AI driven solutions and seeking to optimise the automation of the accounting process and elevate the standard of professional service delivered. |
