Submit your papersSubmit Now
For Enquiries: [email protected]
IIARD LogoIIARD

Accounting Measures and Process Automation Dividends and Challenges

Dr. Tonye Okiriki, Ateh Warefiniere

Abstract

The integration of process automation in accounting has reshaped the traditional landscape, bringing both efficiency and challenges. This paper explores the dividends of automating accounting processes, including enhanced accuracy, time savings, cost reductions, and improved decision-making. By utilizing advanced technologies such as artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA), organizations can streamline routine tasks like payroll, invoicing, and financial reporting. Automation minimizes human error, boosts data analysis capabilities, and ensures compliance with evolving regulatory requirements. However, the shift to automation also presents significant challenges. These include the initial costs of implementation, the need for continuous software updates, and the risk of cyber security threats. Additionally, organizations must address concerns about workforce displacement and the requirement for re skilling employees to manage and interact with automated systems. Furthermore, integrating automation into existing accounting systems can create complexities that demand a robust change management approach. This paper reviews the dividends of accounting process automation while acknowledging the operational, ethical, and technological challenges that arise. In conclusion, while automation promises transformative gains, businesses must carefully navigate the challenges to fully realize its

Keywords

Accounting measureProcess AutomationdividendsChallenges.

References

Arney, J. B. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), 99-120. Brown, A. (2024). Real-time financial analysis and process automation. Journal of Accounting Technology, 29(3), 45-58. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Science, 38(8), 975-1003. Davis, R., & Lee, M. (2023). Cost savings and operational efficiency through accounting automation. Financial Management Review, 32(2), 112-127. Deloitte. (2023). Global Robotic Process Automation Survey. Deloitte Insights. Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs, and ownership structure. Journal of Financial Economics, 3(4), 305-360. Jones, T., & Roberts, K. (2023). Challenges in implementing accounting automation: Data security and training. International Journal of Accounting Information Systems, 21 Jones, T., & Smith, K. (2022). System reliability in automated accounting: Challenges and solutions. Journal of Accounting Systems, 25(2), 145-159. Laux, C., &Leuz, C. (2009). The crisis of fair-value accounting: Making sense of the recent debate. Accounting, Organisations and Society, 34(6-7), 826-834. Lawrence, P. R., & Lorsch, J. W. (1967). Organisation and Environment: Managing Differentiation and Integration. Harvard University Press. Liu, Y., Zhang, X., & Wang, H. (2023). Training and skill requirements for accounting automation: An empirical study. Accounting Education Journal, 22(3), 88-104. Ng, H., & Chye, K. (2021). The impact of Robotic Process Automation on accounting accuracy and efficiency. International Journal of Accounting and Information Management, 29(4), 305-321. Patel, R., & Mistry, M. (2022). Cost implications of accounting automation: A case study. Financial Management Review, 31(1), 56-72. Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press. Schipper, K., & Vincent, L. (2003). Earnings quality. Accounting Horizons, 17(sup1), 97-110. Smith, J. (2022). Efficiency and accuracy in accounting through automation. Accounting Innovations Quarterly, 18(1), 22-37. Smith, J., & Li, X. (2024). Data security challenges in automated accounting systems. Journal of Financial Data Security, 19(1), 42-59. Stewart, G. B. (1991). The Quest for Value: A Guide for Senior Managers. HarperBusiness Wang, T., & Wang, Y. (2022). Enhancing financial forecasting through AI-driven automation. Journal of Financial Analytics, 30(2), 123-137.

More Articles from WORLD JOURNAL OF ENTREPRENEURIAL DEVELOPMENT STUDIES