PRIMENA VEŠTAČKE INTELIGENCIJE U RAČUNOVODSTVU I REVIZIJI: PREGLED SAVREMENIH ISTRAŽIVANJA I PRAKTIČNE IMPLIKACIJE

Računovodstvena znanja kao činilac ekonomskog i društvenog napretka (2026) [pp. 241-250]  

AUTHOR(S) / AUTOR(I): Dragana Đorđević , Sunčica Milutinović , Ivana Medved , Nikola Rakić
Download Full Pdf   
DOI: https://doi.org/10.46793/RZ26.241DJ
ABSTRACT / SAŽETAK:

Primena veštačke inteligencije (AI) u računovodstvu i reviziji značajno menja profesionalnu praksu, omogućavajući automatizaciju rutinskih zadataka, unapređenje tačnosti finansijskih podataka i podršku strateškom odlučivanju kroz prediktivnu analitiku. Ovaj rad predstavlja sistematski pregled savremenih istraživanja objavljenih u periodu od 2015. do 2025. godine, fokusiran na ključne trendove, prednosti, izazove i praktične implikacije AI tehnologija. Analiza pokazuje da AI povećava efikasnost i kvalitet finansijskog izveštavanja, podržava kontinuiranu reviziju i transformiše profesionalne kompetencije stručnjaka. Istovremeno, istaknuti su etički, regulatorni i organizacioni izazovi, uključujući transparentnost algoritama, upravljanje podacima i razvoj digitalnih veština. Zaključci ukazuju da odgovorna i promišljena implementacija AI tehnologija može unaprediti konkurentnost organizacija i kvalitet poslovnih odluka, ali zahteva balansiranje tehnoloških inovacija sa ljudskom ekspertizom i profesionalnim standardima.

KEYWORDS / KLJUČNE REČI:

veštačka inteligencija, računovodstvo, finansijsko izveštavanje, revizija, automatizacija

ACKNOWLEDGEMENT / PROJEKAT:
REFERENCES / LITERATURA:
  • Al-Htaybat, K., von Alberti-Alhtaybat, L., & Alhatabat, Z. (2018). Educating digital natives for the future: Accounting educators’ evaluation of the accounting curriculum. Accounting Education, 27(4), 333-357.
  • Alles, M. (2015). Drivers of the use and facilitators and obstacles of the evolution of big data by the audit profession. Accounting Horizons, 29(2), 439-449.
  •  Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big data and analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice & Theory, 36(4), 1-27.
  • Barocas, S., & Selbst, A. D. (2016). Big data’s disparate impact. California Law Review, 104(3), 671-732.
  • Brougham, D., & Haar, J. (2018). Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management & Organization, 24(2), 239-257.
  • Brown-Liburd, H., Issa, H., & Lombardi, D. (2015). Behavioral implications of big data’s impact on audit judgment and decision making and future research directions. Accounting Horizons, 29(2), 451-468. 
  • Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence. Harvard Business Review. Preuzeto sa: https://hbr.org/2017/07/the–business–ofartificial–intelligence (25.03.2026).
  • Brynjolfsson, E., Rock, D., & Syverson, C. (2021). The productivity J-curve: How intangibles complement general purpose technologies. American Economic Journal: Macroeconomics, 13(1), 333-372. 
  • Bughin, J., Seong, J., Manyika, J., Chui, M., & Joshi, R. (2018). Artificial intelligence: The next digital frontier?. McKinsey Global Institute. 
  • Cao, M., Chychyla, R., & Stewart, T. (2015). Big data analytics in financial statement audits. Accounting Horizons, 29(2), 423-429.
  • Daud, D., Kishan, K., & Azhar, Z. (2024). A systematic review on ethical challenges of emerging AI in accounting using the ado model. International Journal of Research and Innovation in Social Science, 8(19), 87-104. 
  • Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review. Preuzeto sa: https://hbr.org/2018/01/artificialintelligence–for–the–real–world (25.03.2026).
  • Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan,
  • Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen,
  • M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B.,
  • Medaglia, R., …, & Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
  • Felzmann, H., Villaronga, E. F., Lutz, C., & Tamò-Larrieux, A. (2020). Towards transparency by design for artificial intelligence. Science and Engineering Ethics, 26(6), 3333-3361.
  • Floridi, L., Cowls., J., Beltranetti, M., Chatila, R., Chazerand, R., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., &
  • Vayena, E. (2018). AI4People – An Ethical Framework for a Good AI Society:
  • Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689-707.
  • Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological Forecasting and Social Change, 114, 254-280.
  • Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big Data Techniques in Auditing Research and Practice: Current Trends and Future Opportunities. Journal of Accounting Literature, 40, 102-115.
  • Issa, H., Sun, T., & Vasarhelyi, M. A. (2016). Research ideas for artificial intelligence in auditing: The formalization of audit and workforce supplementation. Journal of Emerging Technologies in Accounting, 13(2), 1-20.
  • Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586. 
  • Kerr, D. S., Smith, K. T., Smith, L. M., & Xu, T. (2025). A review of AI and its impact on management accounting and society. Journal of Risk and Financial Management, 18(6), 340.
  • Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115-122.
  • Kroll, J., Huey, J., Barocas, S., Felten, E., Reidenberg, J., Robinson, D., & Yu, H. (2017). Accountable algorithms. University of Pennsylvania Law Review, 165, 633-705.
  • Kuenkaikaew, S., & Vasarhelyi, M. (2012). The predictive audit framework. The International Journal of Digital Accounting Research, 13, 37-71. Preuzeto sa: https://www.uhu.es/ijdar/10.4192/1577–8517–v13_2.pdf (25.03.2026).
  • Kureljusic M., & Karger, E. (2023). Forecasting in financial accounting with artificial intelligence: A systematic literature review and future research agenda. Journal of Applied Accounting Research, 25(1), 81-104.
  • Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60. 
  • Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 1-21. 
  • Moll, J., & Yigitbasioglu, O. (2019). The role of internet-related technologies in shaping the work of accountants: New directions for accounting research. The British Accounting Review, 51(6), 100833. 
  • Odonkor, B., Kaggwa, S., Uwaoma, P. U., Hassan, A. O., & Farayola, O. A. (2024). The impact of AI on accounting practices: A review. World Journal of Advanced Research and Reviews, 21(1), 172-188. 
  • Omoteso, K. (2012). The application of artificial intelligence in auditing: Looking back to the future. Expert Systems with Applications, 39(9), 8490-8495.
  • Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review, 46(1), 192-210.
  • Ransbotham, S., Kiron, D., Gerbert, P., & Reeves, M. (2017). Reshaping business with artificial intelligence. MIT Sloan Management Review, 59(1), 1-20. 
  • Richins, G., Stapleton, A., Stratopoulos, T. C., & Wong, C. (2017). Big data analytics: Opportunity or threat for the accounting profession?. Journal of Information Systems, 31(3), 63-79.
  • Rozario, A. M., & Vasarhelyi, M. A. (2018). Auditing with smart contracts. International Journal of Digital Accounting Research, 18, 1-27. 
  • Siau, K., & Wang, W. (2020). Artificial intelligence (AI) ethics: Ethics of AI and ethical AI. Journal of Database Management, 31(2), 74-87.
  • Sowa, K., Przegalinska, A., & Ciechanowski, L. (2021). Cobots in knowledge work: Human–AI collaboration in managerial professions. Journal of Business Research, 125, 135-142.
  • Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of artificial intelligence in the public sector. Government Information Quarterly, 36(2), 368-383. 
  • Sutton, S. G., Holt, M., & Arnold, V. (2016). The reports of my death are greatly exaggerated – Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60-73.
  • Weheba, M. A. M. (2024). The application of artificial intelligence in accounting and auditing: A narrative literature review. Scientific Journal of Financial and Administrative Studies, 16(6), 1203-1222. 
  • Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review. Preuzeto sa: https://hbr.org/2018/07/collaborative–intelligence–humans–and–ai–are–joiningforces (25.03.2026).
Post Views: 8