Acta academica karviniensia 2026, 26(1):65-76 | DOI: 10.25142/aak.2026.005
The Future of Accounting: Determinants of Artificial Intelligence Adoption
- Technical University of Ostrava, Faculty of Economics, 17. listopadu 2172/15, 708 00 Ostrava-Poruba
The rapid development of artificial intelligence is fundamentally transforming the accounting profession by enabling the automation of routine processes, increasing efficiency, and improving the quality of decision-making. Nevertheless, its adoption in practice remains uneven, indicating the existence of various barriers and factors influencing its acceptance. The aim of this study was to identify and analyze the key factors affecting the intention to use artificial intelligence in accounting by applying technology acceptance models and extending them with factors relevant to the accounting environment. The empirical part of the research was based on a questionnaire survey conducted among respondents working in the field of accounting. The data were analyzed using Principal Component Analysis and linear regression analysis in order to identify underlying components and examine their influence on the intention to use artificial intelligence. The results indicated that the model explained 64.4% of the variance in the intention to use artificial intelligence. Perceived usefulness, facilitating conditions, and perceived risk were identified as statistically significant factors. Perceived usefulness and facilitating conditions exerted a positive influence, whereas perceived risk had a negative effect. Trust and social influence were not found to be statistically significant determinants. The findings suggest that the adoption of artificial intelligence in accounting is driven primarily by the rational evaluation of perceived benefits and risks rather than by the social environment or general trust in the technology.
Keywords: accounting, artificial intelligence, behavioral intention, perceived risk, perceived usefulness, technology acceptance.
JEL classification: C38, M41, O33
Received: May 15, 2026; Revised: June 2, 2026; Accepted: June 10, 2026; Published: June 12, 2026 Show citation
References
- Abu Afifa, M. M., Van, H. V., & Van, T. L. H. (2023). Blockchain adoption in accounting by an extended UTAUT model: Empirical evidence from an emerging economy. Journal of Financial Reporting and Accounting, 21(1), 5-44. https://doi.org/10.1108/JFRA-12-2021-0434
Go to original source... - Adamek, J., & Solarz, M. (2025). Determinants of artificial intelligence use by accounting practitioners from the perspective of the technology readiness and acceptance model (TRAM). Zeszyty Teoretyczne Rachunkowo¶ci, 49(2), 11-36. https://doi.org/10.5604/01.3001.0055.1484
Go to original source... - Al-Okaily, M. (2025). Evaluation of intelligent accounting systems usage among SMEs: An empirical investigation. Global Knowledge, Memory and Communication. https://doi.org/10.1108/GKMC-12-2024-0839
Go to original source... - Almgrashi, A., & Mujalli, A. (2025). Sustainable transformation of the accounting and auditing profession: Readiness for blockchain technology adoption through UTAUT and TAM3 frameworks. Sustainability, 17(23), Article 10811. https://doi.org/10.3390/su172310811
Go to original source... - Almgrashi, A., Mujalli, A., Khan, T., & Attia, O. (2023). Factors determining internal auditors' behavioral intention to use computer-assisted auditing techniques: An extension of the UTAUT model and an empirical study. Future Business Journal, 9(1), Article 74. https://doi.org/10.1186/s43093-023-00231-2
Go to original source... - AlNasrallah, W., & Saleem, F. (2022). Determinants of the digitalization of accounting in an emerging market: The roles of organizational support and job relevance. Sustainability, 14(11), Article 6483. https://doi.org/10.3390/su14116483
Go to original source... - Andrlík, B., Mokrý, S., & David, P. (2023). The indirect administrative burden of road tax proposal: Survey and eye-tracking experiment in the Czech Republic. Acta Academica Karviniensia, 23(2), 5-17. https://doi.org/10.25142/aak.2023.011
Go to original source... - Cheng, G., & Shao, Y. G. (2022). Influencing factors of accounting practitioners' acceptance of mobile learning. International Journal of Emerging Technologies in Learning, 17(1), 90-101. https://doi.org/10.3991/ijet.v17i01.28465
Go to original source... - Glacová, K., & Turečková, K. (2024). The theory of learning regions in the context of measurable indicators for the NUTS3 level on the example of the Czech Republic. Acta Academica Karviniensia, 24(2), 5-15. https://doi.org/10.25142/aak.2024.007
Go to original source... - Jackson, D., & Allen, C. (2024). Technology adoption in accounting: The role of staff perceptions and organisational context. Journal of Accounting and Organizational Change, 20(2), 205-227. https://doi.org/10.1108/JAOC-01-2023-0007
Go to original source... - Jena, R. K. (2024). Investigating accounting professionals' intention to adopt blockchain technology. Review of Accounting and Finance, 23(3), 375-393. https://doi.org/10.1108/RAF-06-2023-0185
Go to original source... - Lutfi, A. (2022). Factors influencing the continuance intention to use accounting information system in Jordanian SMEs from the perspectives of UTAUT: Top management support and self-efficacy as predictor factors. Economies, 10(4), Article 75. https://doi.org/10.3390/economies10040075
Go to original source... - Moore, D. S., & Notz, W. (2020). Statistics: Concepts and controversies (10th ed.). Macmillan International Higher Education.
- Petrová, P. (2025). Changes in the business valuation process and accounting with regard to digitalisation and automation of processes. Acta Academica Karviniensia, 25(2), 32-42. https://doi.org/10.25142/aak.2025.010
Go to original source... - Phu, N. G., Thi, T. H., & Bich, H. T. N. (2025). The impact of cloud computing technology on cloud accounting adoption and financial management of businesses. Humanities & Social Sciences Communications, 12(1), Article 851. https://doi.org/10.1057/s41599-025-05190-3
Go to original source... - Predkiewicz, K., & Biegun, K. (2025). Factors that influence accountants' acceptance of artificial intelligence: An extended Technology Acceptance Model that incorporates technology anxiety and experience. Zeszyty Teoretyczne Rachunkowo¶ci, 49(4), 147-168. https://doi.org/10.5604/01.3001.0055.4527
Go to original source... - Pramuka, B. A., & Pinasti, M. (2020). Does cloud-based accounting information system harmonize the small business needs? Journal of Information and Organizational Sciences, 44(1), 141-156. https://doi.org/10.31341/jios.44.1.6
Go to original source... - Salat, D. (2024). Does entrepreneurial education support start-up spirit of students? Case of the School of Business Administration in Karviná. Acta Academica Karviniensia, 24(2), 42-53. https://doi.org/10.25142/aak.2024.010
Go to original source... - Salmen, A. (2022). Employing RPA and AI to automize order entry process with individual and small-sized structures: A SME business case study. Acta Academica Karviniensia, 22(2), 78-96. https://doi.org/10.25142/aak.2022.017
Go to original source... - Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Go to original source... - Yusuf, Y. T. N., Mediaty, & Mas'ud, A. A. (2025). Technology acceptance and financial reporting quality: The unfulfilled moderating role of HR competence. Veredas do Direito, 22, Article e223115. https://doi.org/10.18623/rvd.v22.n6.3115
Go to original source...



