INTEGRATION OF ARTIFICIAL INTELLIGENCE IN MANAGEMENT ACCOUNTING: A SWOT ANALYSIS

Abstract

Today, information is the source of competitive advantage and businesses need to create information architecture that will enable them to make the right decisions in the fastest way. For this reason, it seems inevitable that businesses will reshape their entire business environments in a way that will create far-reaching consequences on business processes and prioritize technological progress by investing in artificial intelligence (AI) applications to create value with better performance. Management accounting is a business function that is central to identifying, collecting, measuring, and analyzing data. Therefore, these developments are expected to change management accounting practices and the roles of management accountants within the business. Although it is predicted that the main function of accounting in the future will be to create real-time value for the business by combining management accounting applications with AI, this combination also carries the potential to create significant problems. The purpose of this study is to conduct a SWOT analysis and examine the strengths and weaknesses of the use of AI in management accounting and the opportunities and threats that may arise as a result of this integration.

Keywords

• Management accounting
• Artificial intelligence
• AI
• Machine learning
• SWOT analysis

References

1. Aaser, M. & McElhaney, D. (2021). Harnessing the power of external data. McKinsey Technology.
2. Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25: 29–44.
3. Bertomeu, J., Cheynel, E., Floyd, E., & Pan, W. (2021). Using machine learning to detect misstatements. Review of Accounting Studies, 26(2): 468–519.
4. Bhimani, A. & Willcocks, L. (2014). Digitisation, “Bigdata” and the transformation of accounting information. Accounting and Business Research, 44(4): 469–490.
5. Bose, S., Dey, S. K., & Bhattacharjee, S. (2023). Big data, data analytics and artificial intelligence in accounting: An overview. In S. Akter & S. F. Wamba (Eds.), Handbook of big data methods, pp. 32–51, Edward Elgar Publishing.
6. Caglio, A. (2003). Enterprise resource planning systems and accountants: Towards hybridization? European Accounting Review, 12: 123–153.
7. Ding, K., Lev, B., Peng, X., Sun, T., & Vasarhelyi, M. A. (2020). Machine learning improves accounting estimates: Evidence from insurance payments. Review of Accounting Studies, 25(3): 1098–1134.
8. Elbashir, M.Z., Collier, P.A., Sutton, S.G., Davern, M.J. & Leech, S.A. (2013). Enhancing the business value of business intelligence: The role of shared knowledge and assimilation. Journal of Information Systems, 27(2): 87–105.

9. 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. Gärtner, B. & Hiebl, M.R. (2018). Issues with big data. In Quinn, M. & Strauss, E. (Eds), The Routledge companion to accounting information systems, pp. 161–172, Routledge. Geddes, B. H. (2020). Emerging technologies in management accounting. Journal of Economics and Business, 3(1): 152–159. Granlund, M. & Malmi, T. (2002). Moderate impact of ERPS on management accounting: A lag or permanent outcome? Management Accounting Research, 13: 299–321.
10. Granlund, M. & Teittinen, H. (2017). Accounting information systems and decision-making. In Quinn, M. & Strauss, E. (Eds.), The Routledge companion to accounting information systems, pp. 81–93, Routledge.
11. Jang, H. (2019). A decision support framework for robust R&D budget allocation using machine learning and optimization. Decision Support Systems, 121: 1–12.
12. Johnson, E., Petersen, M., Sloan, J., & Valencia, A. (2021). The interest, knowledge, and usage of artificial intelligence in accounting: Evidence from accounting professionals. Accounting & Taxation, 13(1): 45–58.
13. Kiron, D., Kirk, P., Ferguson, R., (2014). The Analytics Mandate. http://sloanreview.mit.edu/projects/analytics-mandate/ (Accessed on Dec. 10, 2023).
14. Korhonen, T., Selos, E., Laine, T., & Suomala, P. (2021). Exploring the programmability of management accounting work for increasing automation: an interventionist case study. Accounting, Auditing and Accountability Journal, 34(2): 253–280.
15. Kowalczyk, M. & Buxmann, P. (2015). An ambidextrous perspective on business intelligence and analytics support in decision processes: Insights from a multiple case study. Decision Support Systems, 80: 1–13.
16. Küçüker, M. (2023). Muhasebede yapay zekâ uygulamaları: ChatGPT’nin muhasebe sınavı. Fırat Üniversitesi Sosyal Bilimler Dergisi, 33(2): 875–888.
17. Lawson, R. What do management accountants do? IMA. https://business.okstate.edu/site-files/archive/docs/accounting/what-do-management-accountants-do.pdf (Accessed on Dec. 3, 2023). LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521: 436–444.
18. Li, C., Haohao, S., & Ming, F. (2020). Research on the impact of artificial intelligence technology on accounting. Journal of Physics: Conference Series, 1486, 032042.
19. Mayer-Schönberger, V. & Cukier, K. (2013). Big data: A revolution that will transform how we live, work and think. John Murray, London.
20. 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.
21. Nielsen, S. (2022). Management accounting and the concepts of exploratory data analysis and unsupervised machine learning: A literature study and future directions. Journal of Accounting & Organizational Change, 18(5): 811–853.
22. Norvig, P. & Russell, S. J. (2009). Artificial intelligence: A modern approach. Prentice Hall.
23. Odonkor, B., Kaggwa, S., Uwaoma, P. U., Hassan, A. O., & Farayola, O. A. (2024). The impact of AI on accounting practices: A review: Exploring how artificial intelligence is transforming traditional accounting methods and financial reporting. World Journal of Advanced Research and Reviews, 21(1): 172–188.
24. Quattrone, P. (2016). Management accounting goes digital: Will the move make it wiser? Management Accounting Research, 31: 118–122.
25. Ranta, M., Ylinen, M., & Järvenpää, M. (2023). Machine learning in management accounting research: Literature review and pathways for the future. European Accounting Review, 32(3): 607–636.
26. Reinsel D., Gantz J., & Rydning J. (2018). The digitization of the world - from edge to core. IDC White Paper. https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf (Accessed on Nov. 12, 2023).
27. Rikhardsson, P. & Yigitbasioglu, Q. (2018). Business intelligence & analytics in management accounting research: Status and future focus. International Journal of Accounting Information Systems, 29: 37–58.
28. Rom, A. & Rohde, C. (2007). Management accounting and integrated information systems: A literature review. International Journal of Accounting Information Systems, 8: 40–68.
29. Schatsky, D., Camhi, J., & Muraskin, C. (2019). Data ecosystems: How third-party information can enhance analytics. Deloitte Insights. https://www2.deloitte.com/content/dam/insights/us/articles/4603_Data-ecosystems/DI_Data-ecosystems.pdf (Accessed on Nov. 19, 2023).
30. Schneider, G. P., Dai, J., Janvrin, D. J., Ajayi, K., & Raschke, R. L. (2015). Infer, predict, and assure: Accounting opportunities in data analytics. Accounting Horizons, 29(3): 719–742.
31. Vărzaru, A.A. (2022). Assessing artificial intelligence technology acceptance in managerial accounting. Electronics, 11(14), 2256.
32. Wang, R. Y. & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems 12(4): 5–33.
33. Warren, J., Donald, J., Moffitt, K.C., & Byrnes, P. (2015). How big data will change accounting. Accounting Horizons, 29(2): 397–407.
34. Zhang, C., Zhu, W., Dai, J., Wu, Y., & Chen, X. (2023). Ethical impact of artificial intelligence in managerial accounting. International Journal of Accounting Information Systems 49, 100619.
35. Zhang, X. (2021). Application of data mining and machine learning in management accounting information system. Journal of Applied Science and Engineering, 24(5): 813–820.