Transformation in Accounting Practices
DOI:
https://doi.org/10.47577/business.v10i.11876Abstract
This paper explores the transformative impact of automation and artificial intelligence (AI) on accounting practices. The integration of AI has shifted accounting from traditional manual tasks to automated processes, enhancing efficiency, accuracy, and scalability. AI-driven systems reduce human errors, ensure compliance, and offer data-driven insights, enabling accountants to take on more strategic advisory roles. Additionally, the adoption of cloud-based solutions allows real-time financial data access, improving decision-making processes. Through a review of real-world applications and the potential challenges, this paper highlights how AI is reshaping financial reporting, auditing, and the future of the accounting profession.
References
Hasan, A. R. (2021). Artificial Intelligence (AI) in accounting & auditing: A Literature review. Open Journal of Business and Management, 10(1), 440-465.
Gotthardt, M., Koivulaakso, D., Paksoy, O., Saramo, C., Martikainen, M., & Lehner, O. (2020). Current state and challenges in the implementation of smart robotic process automation in accounting and auditing. ACRN Journal of Finance and Risk Perspectives.
Halkiopoulos, C., Papadopoulos, A., Stamatiou, Y. C., Theodorakopoulos, L., & Vlachos, V. (2024). A Digital Service for Citizens: Multi-Parameter Optimization Model for Cost-Benefit Analysis of Cybercrime and Cyberdefense. Emerging Science Journal, 8(4), 1320-1344.
Eziefule, A. O., Adelakun, B. O., Okoye, I. N., & Attieku, J. S. (2022). The Role of AI in Automating Routine Accounting Tasks: Efficiency Gains and Workforce Implications. European Journal of Accounting, Auditing and Finance Research, 10(12), 109-134.
Theodorakopoulos, L., Theodoropoulou, A., & Stamatiou, Y. (2024). A State-of-the-Art Review in Big Data Management Engineering: Real-Life Case Studies, Challenges, and Future Research Directions. Eng, 5(3), 1266-1297.
Antonopoulou, H., Theodorakopoulos, L., Halkiopoulos, C., & Mamalougkou, V. (2023). Utilizing machine learning to reassess the predictability of bank stocks. Emerging Science Journal, 7(3), 724-732.
Marshall, T. E., & Lambert, S. L. (2018). Cloud-based intelligent accounting applications: accounting task automation using IBM watson cognitive computing. Journal of emerging technologies in accounting, 15(1), 199-215.
Theodorakopoulos, L., Thanasas, G., & Halkiopoulos, C. (2024). Implications of Big Data in Accounting: Challenges and Opportunities. Emerging Science Journal, 8(3), 1201-1214.
Karras, A., Giannaros, A., Theodorakopoulos, L., Krimpas, G. A., Kalogeratos, G., Karras, C., & Sioutas, S. (2023). FLIBD: A federated learning-based IoT big data management approach for privacy-preserving over Apache Spark with FATE. Electronics, 12(22), 4633.
Thanasas, G. L., Theodorakopoulos, L., & Lampropoulos, S. (2022). A Big Data Analysis with Machine Learning techniques in Accounting dataset from the Greek banking system. European Journal of Accounting, Auditing and Finance Research.
Bavaresco, R. S., Nesi, L. C., Barbosa, J. L. V., Antunes, R. S., da Rosa Righi, R., da Costa, C. A., ... & Moreira, C. (2023). Machine learning-based automation of accounting services: An exploratory case study. International Journal of Accounting Information Systems, 49, 100618.
Karras, C., Karras, A., Theodorakopoulos, L., Giannoukou, I., & Sioutas, S. (2022, August). Expanding queries with maximum likelihood estimators and language models. In The International Conference on Innovations in Computing Research (pp. 201-213). Cham: Springer International Publishing.
Theodorakopoulos, L., Antonopoulou, H., Mamalougou, V., & Giotopoulos, K. (2022). The drivers of volume volatility: A big data analysis based on economic uncertainty measures for the Greek banking system. Available at SSRN 4306619.
Antonopoulou, H., Mamalougou, V., & Theodorakopoulos, L. (2022). The role of economic policy uncertainty in predicting stock return volatility in the banking industry: A big data analysis. Emerging Science Journal, 6(3), 569-577.
Kuaiber, M. Q., Ali, Z. N., Al-Yasiri, A. J., Kareem, A. J., Al, M. A., & Almagtome, A. (2024, April). Automation and the Future of Accounting: A Study of AI Integration in Financial Reporting. In 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS) (Vol. 1, pp. 1-6). IEEE.
Vasilopoulos, C., Theodorakopoulos, L., & Giotopoulos, K. (2023). Big Data and Consumer Behavior: The Power and Pitfalls of Analytics in the Digital Age. Technium Soc. Sci. J., 45, 469.Becken, S. (2019). Virtual reality and tourism: An environmental sustainability perspective. Journal of Sustainable Tourism, 27(4), 551-566.
Theodorakopoulos, L., Theodoropoulou, A., & Halkiopoulos, C. (2024). Enhancing Decentralized Decision-Making with Big Data and Blockchain Technology: A Comprehensive Review. Applied Sciences, 14(16), 7007.
Khaled AlKoheji, A., & Al-Sartawi, A. (2022, May). Artificial intelligence and its impact on accounting systems. In European, Asian, Middle Eastern, North African Conference on Management & Information Systems (pp. 647-655). Cham: Springer International Publishing.
Vasilopoulos, C., Theodorakopoulos, L., & Giotopoulos, K. (2023). The Promise and Peril of Big Data in Driving Consumer Engagement. Technium Soc. Sci. J., 45, 489.
Karras, C., Theodorakopoulos, L., Karras, A., & Krimpas, G. A. (2024). Efficient Algorithms for Range Mode Queries in the Big Data Era. Information, 15(8), 450.
Vasilopoulou, C., Theodorakopoulos, L., & Giotopoulos, K. (2023). Big Data Analytics: A Catalyst for Digital Transformation in e-Government. Technium Social Sciences Journal, 45, 449-459.
Igoumenakis, G., Theodoropoulou, A., & Halkiopoulos, C. (2023, August). Tourism and Developing Countries. Conditions and Prospects for Tourism Development. In International Conference of the International Association of Cultural and Digital Tourism (pp. 721-748). Cham: Springer Nature Switzerland.
Halkiopoulos, C., Igoumenakis, G., & Theodoropoulou, A. (2023, August). Evaluation of Hotel Services Utilizing Digital Marketing Strategies in Less Developed Countries Within the Hospitality Industry. In International Conference of the International Association of Cultural and Digital Tourism (pp. 323-346). Cham: Springer Nature Switzerland.
Oviya, S., Sharadha, N., Bhuvaneswari, E., Vijayalakshmi, S., & Sushma, K. (2024). The Impact of Automation and Ai in Revolutionising Traditional Accounting Methods. Journal of Informatics Education and Research, 4(2).
Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A profession in transition: actors, tasks and roles in AI-based accounting. Journal of Applied Accounting Research, 22(3), 539-556.
Srbinoska, D. S., & Donovska, S. (2023). AUTOMATION OF ACCOUNTING PROCESSES: THE IMPACT OF ARTIFICIAL INTELLIGENCE AND ERP SYSTEMS ON ACCOUNTING. Proceedings of the Faculty of Economics & Business in Zagreb/Zbornik Ekonomskog Fakulteta u Zagrebu, 21(2).
Jędrzejka, D. (2019). Robotic process automation and its impact on accounting. Zeszyty Teoretyczne Rachunkowości, (105), 137-166.
Kaya, C. T., Türkyılmaz, M., & Birol, B. (2019). Impact of RPA technologies on accounting systems. Muhasebe ve Finansman Dergisi, (82).
Karbekova, A. B., Мakhkamova, S. G., Inkova, N. A., & Pakhomova, O. K. (2023). Automation based on datasets and ai of corporate accounting and sustainability reporting in quality management in industry 4.0. Proceedings on Engineering Sciences, 5(S2), 265-278.
Nakano, M. (2022). Artificial intelligence and robotic process automation for accounting and auditing in society 5.0. 社会科学ジャーナル, (89), 51-61.
Rawashdeh, A., Bakhit, M., & Abaalkhail, L. (2023). Determinants of artificial intelligence adoption in SMEs: The mediating role of accounting automation. International Journal of Data and Network Science, 7(1), 25-34.
Morrison, M. (2019). Risk management in automation of the accounting process. In Multiple Perspectives in Risk and Risk Management: ERRN 8th European Risk Conference 2018, Katowice, Poland, September 20-21 (pp. 231-239). Springer International Publishing.
Dong, X. L., & Rekatsinas, T. (2018, May). Data integration and machine learning: A natural synergy. In Proceedings of the 2018 international conference on management of data (pp. 1645-1650).
Wu, L., Li, Z., & AbouRizk, S. (2022). Automating common data integration for improved data-driven decision-support system in industrial construction. Journal of Computing in Civil Engineering, 36(2), 04021037.
Miller, D. A., Pacifici, K., Sanderlin, J. S., & Reich, B. J. (2019). The recent past and promising future for data integration methods to estimate species’ distributions. Methods in Ecology and Evolution, 10(1), 22-37.
Böhm, T. (2012). Accuracy improvement of condition diagnosis of railway switches via external data integration. Structural health monitoring, 1550-1558.
Peddle, D. R., & Franklin, S. E. (1991). Lmage texture processing and data integration. Photogrammetric Engineering and Remote Sensing, 57, 413-420.
Singh, N., Lai, K. H., Vejvar, M., & Cheng, T. E. (2019). Data‐driven auditing: A predictive modeling approach to fraud detection and classification. Journal of Corporate Accounting & Finance, 30(3), 64-82.
Zhao, H., & Wang, Y. (2023). A Big Data-Driven Financial Auditing Method Using Convolution Neural Network. IEEE Access, 11, 41492-41502.
Handoko, B. L., Mulyawan, A. N., Tanuwijaya, J., & Tanciady, F. (2020). Big data in auditing for the future of data driven fraud detection. International Journal of Innovative Technology and Exploring Engineering, 9(3), 2902-2907.
Olha, K., & Yevgen, K. (2024). OVERVIEW OF THE INTELLIGENT DATA ANALYSIS IN THE DATA-DRIVEN AUDITING PRACTICES. Ш94 Штучний інтелект у науці та освіті (AISE 2024). Artificial intelligence in science and education: збірник матеріалів міжнародної наукової конференції (Київ, 1-2 березня 2024 р.)[Електронний ресурс]/[упоряд: А. Яцишин, В. Матусевич, В. Коваленко].–Київ: УкрІНТЕІ, 2024.–600 с., 463.
Nonnenmacher, J., Kruse, F., Schumann, G., & Marx Gómez, J. (2021). Using autoencoders for data-driven analysis in internal auditing.
Sliunina, T., Rozit, T., Kosata, I., Ponomarova, T., & Tiurina, D. (2024). Innovative Approaches to Data Analysis in Accounting and Auditing (From Big Data to Data-Driven Solutions). Pacific Business Review International, 16(10).
Ahmad, A., Saad, M., Njilla, L., Kamhoua, C., Bassiouni, M., & Mohaisen, A. (2019, May). Blocktrail: A scalable multichain solution for blockchain-based audit trails. In ICC 2019-2019 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.
Snow, P., Deery, B., Lu, J., Johnston, D., Kirby, P., Sprague, A. Y., & Byington, D. (2014). Business processes secured by immutable audit trails on the blockchain. Brave New Coin.
Sahlin, E., & Levenby, R. (2018). Blockchain in audit trails: An investigation of how blockchain can help auditors to implement audit trails.
Ahmad, A., Saad, M., Al Ghamdi, M., Nyang, D., & Mohaisen, D. (2021). Blocktrail: A service for secure and transparent blockchain-driven audit trails. IEEE Systems Journal, 16(1), 1367-1378.
Regueiro, C., Seco, I., Gutiérrez-Agüero, I., Urquizu, B., & Mansell, J. (2021). A blockchain-based audit trail mechanism: Design and implementation. Algorithms, 14(12), 341.
Hofmann, B. (2021). Privacy enhancing audit trail in hyperledger blockchain (Doctoral dissertation, Hochschule für angewandte Wissenschaften Kempten).
Gokoglan, K., Cetın, S., & Bılen, A. (2022). Blockchain technology and its impact on audit activities. Journal of Economics Finance and Accounting, 9(2), 72-81.
McDaniel, L. S. (1990). The effects of time pressure and audit program structure on audit performance. Journal of Accounting Research, 28(2), 267-285.
Chun, H. M., & Rhee, C. S. (2015). Analyst coverage and audit efforts: empirical approach to audit hours. Journal of Applied Business Research, 31(3), 795.
Herbert, A., Anshu, Gregory, M., Gupta, S. S., & Singh, N. (2009). Invasive cervical cancer audit: a relative increase in interval cancers while coverage increased and incidence declined. BJOG: An International Journal of Obstetrics & Gynaecology, 116(6), 845-853.
Saloner, B., Polsky, D., Friedman, A., & Rhodes, K. (2015). Primary care appointment availability and preventive care utilization: Evidence from an audit study. Medical Care Research and Review, 72(2), 149-167.
Joe, J. R. (2003). Why press coverage of a client influences the audit opinion. Journal of Accounting Research, 41(1), 109-133.
Ashton, R. H., Graul, P. R., & Newton, J. D. (1989). Audit delay and the timeliness of corporate reporting. Contemporary accounting research, 5(2), 657-673.
Ege, M. S., & Stuber, S. B. (2022). Are auditors rewarded for low audit quality? The case of auditor lenience in the insurance industry. Journal of Accounting and Economics, 73(1), 101424.
Chen, J. J., & Zhang, H. (2010). The impact of regulatory enforcement and audit upon IFRS compliance–Evidence from China. European Accounting Review, 19(4), 665-692.
Kwon, J., & Eric, J. M. (2011, December). The Impact of Security Practices on Regulatory Compliance and Security Performance. In ICIS.
Oguejiofor, B. B., Omotosho, A., Abioye, K. M., Alabi, A. M., Oguntoyinbo, F. N., Daraojimba, A. I., & Daraojimba, C. (2023). A review on data-driven regulatory compliance in Nigeria. International Journal of applied research in social sciences, 5(8), 231-243.
Mehrfard, H., & Hamou-Lhadj, A. (2011). The impact of regulatory compliance on Agile software processes with a focus on the FDA guidelines for medical device software. International Journal of Information System Modeling and Design (IJISMD), 2(2), 67-81.
Botelho, A. (2013). The impact of regulatory compliance behavior on hazardous waste generation in European private healthcare facilities. Waste management & research, 31(10), 996-1001.
Brown, M. A., Clarkson, B. D., Barton, B. J., & Joshi, C. (2013). Ecological compensation: an evaluation of regulatory compliance in New Zealand. Impact Assessment and Project Appraisal, 31(1), 34-44.
Wylde, V., Rawindaran, N., Lawrence, J., Balasubramanian, R., Prakash, E., Jayal, A., ... & Platts, J. (2022). Cybersecurity, data privacy and blockchain: A review. SN computer science, 3(2), 127.
Habibzadeh, H., Nussbaum, B. H., Anjomshoa, F., Kantarci, B., & Soyata, T. (2019). A survey on cybersecurity, data privacy, and policy issues in cyber-physical system deployments in smart cities. Sustainable Cities and Society, 50, 101660.
Javid, T., Faris, M., Beenish, H., & Fahad, M. (2020, September). Cybersecurity and data privacy in the cloudlet for preliminary healthcare big data analytics. In 2020 international conference on computing and information technology (ICCIT-1441) (pp. 1-4). IEEE.
Black, K. D., Alam, C. B., Bucher, S. M., Giannetti, A. J., Godfrey, L. D., & Wear, J. D. (2019). Recent developments in cybersecurity and data privacy. Tort Trial & Insurance Practice Law Journal, 54(2), 403-434.
Muhammad, S., Meerjat, F., Meerjat, A., & Dalal, A. (2024). Safeguarding Data Privacy: Enhancing Cybersecurity Measures for Protecting Personal Data in the United States. International Journal of Machine Learning Research in Cybersecurity and Artificial Intelligence, 15(1), 141-176.
McGuinness, S., & Ortiz, L. (2016). Skill gaps in the workplace: measurement, determinants and impacts. Industrial relations journal, 47(3), 253-278.
Cappelli, P. H. (2015). Skill gaps, skill shortages, and skill mismatches: Evidence and arguments for the United States. ILR review, 68(2), 251-290.
Restuccia, D., & Taska, B. (2018, July). Different skills, different gaps: Measuring and closing the skills gap. In Developing skills in a changing world of work (pp. 207-226). Rainer Hampp Verlag.
Osterman, P., & Weaver, A. (2014). Skills and skill gaps in manufacturing.
Arifin, S. R. M. (2018). Ethical considerations in qualitative study. International journal of care scholars, 1(2), 30-33.
Walker, W. (2007). Ethical considerations in phenomenological research. Nurse researcher, 14(3).
Cacciattolo, M. (2015). Ethical considerations in research. In The Praxis of English Language Teaching and Learning (PELT) (pp. 55-73). Brill.
Ketefian, S. (2015). Ethical considerations in research. Focus on vulnerable groups. Investigación y Educación en Enfermería, 33(1), 164-172.
Duclos, P., Okwo-Bele, J. M., & Salisbury, D. (2011). Establishing global policy recommendations: the role of the Strategic Advisory Group of Experts on immunization. Expert review of vaccines, 10(2), 163-173.
Fobé, E., Brans, M., Vancoppenolle, D., & Van Damme, J. (2013). Institutionalized advisory systems: An analysis of member satisfaction of advice production and use across 9 strategic advisory councils in Flanders (Belgium). Policy and Society, 32(3), 225-240.
Stensaker, B., Jungblut, J., & Mihut, G. (2024). Strategic advisory boards–the emergence of shadow governance in universities?. International Journal of Leadership in Education, 27(4), 762-778.
Filippov, S., van der Weg, R., van Ogtrop, F., Beelen, P., & Mooi, H. (2014). Exploring the project portfolio manager's role: Between a data manager and a strategic advisor. Procedia-Social and Behavioral Sciences, 119, 95-104.
Kowalkowski, C., Brehmer, P. O., & Kindstrom, D. (2009). Managing industrial service offerings: requirements on content and processes. International Journal of Services Technology and Management, 11(1), 42-63.
Menor, L. J., Tatikonda, M. V., & Sampson, S. E. (2002). New service development: areas for exploitation and exploration. Journal of Operations Management, 20(2), 135-157.
Johansson, P., & Olhager, J. (2004). Industrial service profiling: Matching service offerings and processes. International Journal of Production Economics, 89(3), 309-320.
De Jong, J. P., & Vermeulen, P. A. (2003). Organizing successful new service development: a literature review. Management decision, 41(9), 844-858.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Georgios L. Thanasas, Georgios Kampiotis
This work is licensed under a Creative Commons Attribution 4.0 International License.