Abstract

In the past, businesses had to rely on manual bookkeeping, which meant writing down every single transaction by hand and double-checking everything to avoid mistakes. Imagine how frustrating it would be for an individual or a group of people to slowly keep such records. And the worst of it is the fact that their chances of getting it wrong would be very high. After this phase, the computer systems were introduced, which made it faster to record transactions and create reports. These systems worked well for many years and helped businesses keep track of their money more efficiently. However, today’s business environment is very different. Companies deal with much more data, they operate in multiple countries, and they face stricter rules and regulations. Old systems were not built to handle this scale and pace. According to Warren, Reeve, and Duchac, global markets have created pressures that older reporting systems cannot manage, leaving many organizations looking for smarter ways to keep their financial information accurate and useful.

Keywords

  • business efficiency
  • General Department of Defense Industry enterprises
  • operational capacity

References

  1. 1. Alles, M. G. (2015). Drivers of the use and facilitators and obstacles of the evolution toward real-time accounting. Accounting Horizons, 29(2), 439–450. [https://doi.org/10.2308/acch-51071](https://doi.org/10.2308/acch-51071)
  2. 2. 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. [https://doi.org/10.2308/ajpt-51812](https://doi.org/10.2308/ajpt-51812)
  3. 3. Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W.W. Norton & Company.
  4. 4. Deloitte. (2021). AI in audit: Transforming the financial reporting process. Deloitte Insights. [https://www2.deloitte.com](https://www2.deloitte.com)
  5. 5. Ghosh, A., & Scott, R. (2022). AI in accounting and auditing: Current applications and challenges. Journal of Accounting Technology, 14(3), 45–62.
  6. 6. IBM. (2021). AI for finance: Automating financial operations. IBM Research. [https://www.ibm.com/research](https://www.ibm.com/research)
  7. 7. IFAC. (2020). Artificial intelligence in accounting: Implications for professional accountants. International Federation of Accountants. [https://www.ifac.org](https://www.ifac.org)
  8. 8. 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. [https://doi.org/10.2308/jeta-10510](https://doi.org/10.2308/jeta-10510)
  9. 9. JP Morgan. (2020). AI applications in finance: Case studies and insights. JP Morgan Research. [https://www.jpmorgan.com/research](https://www.jpmorgan.com/research)
  10. 10. Kogan, A., Levin, A., & Vasarhelyi, M. A. (2019). Machine learning in auditing: A review and future directions. Accounting Horizons, 33(4), 1–20. [https://doi.org/10.2308/acch-52412](https://doi.org/10.2308/acch-52412)
  11. 11. 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. [https://doi.org/10.2308/jeta-51819](https://doi.org/10.2308/jeta-51819)
  12. 12. 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. [https://doi.org/10.1016/j.bar.2019.03.004](https://doi.org/10.1016/j.bar.2019.03.004)
  13. 13. PwC. (2022). AI and auditing: Driving smarter, faster insights. PwC Insights. [https://www.pwc.com](https://www.pwc.com)
  14. 14. Vasarhelyi, M. A., Kogan, A., & Tuttle, B. (2015). Big data in accounting: An overview. Accounting Horizons, 29(2), 381–396. [https://doi.org/10.2308/acch-51069](https://doi.org/10.2308/acch-51069)
  15. 15. Wang, Y., & Siau, K. (2021). Ethical and governance challenges of AI in finance. Journal of Business Ethics, 168, 637–655. [https://doi.org/10.1007/s10551-019-04358-0](https://doi.org/10.1007/s10551-019-04358-0)