Artificial Intelligence and Accountant’s Efficiency: Comparison
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Accounting is one of the basic functions of an organization, assists financial management, decision-making, tax compliance, budgeting, performance evaluation, and corporate governance. Artificial intelligence (AI) is emerging as a disruptive force in many sectors, and using it in accounting isn’t an exception.

  • artificial intelligence
  • accounting
  • sustainability
  • automation
  • accountant’s efficiency

1. Artificial Intelligence in Accounting

Artificial intelligence (AI) is having a great impact on accounting practises, transforming traditional methods and improving overall accuracy and effectiveness [20][1]. For example, AI has enabled data entry and filtering in an automated way [21][2]. It enhances bank reconciliations, reducing errors and enabling accountants to focus on analytical and value-added tasks in their job. AI-powered data analysis enables accountants to effectively handle large volumes of financial data and determine useful insights, which enhances taking decisions and enables them to give clients accurate and strategic financial advice [22][3]. Another possible application for AI in accounting is fraud detection, as it continuously examines financial transactions and detects suspicious activity instantaneously. Early identification of fraudulent activity helps to avert major monetary damages and protects firms’ financial integrity [23][4]. AI also makes financial reporting easier through standardised and accurate reports procedures that ensure adherence to accounting laws and regulations and decreases the effort of manual reporting activities while improving financial statement reliability [24,25][5][6]. AI’s predictive powers play an important role in forecasting and budgeting and empower firms to generate realistic financial estimates and effectively plan for the future [26,27][7][8]. In addition, AI also improves the audit process by automating the process of data verification and validation, resulting in more effective and correct audits [28][9]. The use of AI in accounting has resulted in substantial advances in data analysis, decision-making, automation, fraud detection, etc. In today’s dynamic and data-driven business market, adopting AI technology has become critical for firms to remain competitive and to provide better financial services [29,30][10][11]. In short, the role of AI in accounting is significant and huge. The traditional procedures and activities of accounting functions can be made more effective and efficient through the adoption of innovative AI solutions. From doing automated tasks to fraud detection, from recording data to analyzing for better decisions; all can be done through the use of AI technology in accounting. The adoption of AI in accounting not only makes accounting firms and accountants, more effective and efficient but enhances their productivity and economic growth which also contributes to the attainment of SDGs [18,19][12][13].

2. Automation

AI automation (“the technique of making an apparatus, a process, or a system operate automatically”) [31][14] has various benefits, including increased accuracy, faster operations, real-time reporting, identification of fraud, and better financial analysis in accounting [32][15]. Businesses that embrace AI technology may improve their accounting activities, take more informed decisions, and obtain a competitive advantage in the current data-driven economy [33][16]. For example, one of the major benefits of AI is automated data entry in accounting. With the help of Optical Character Recognition technology, AI-powered systems retrieve information from bills, receipts, and other documents, decreasing the requirement for manually entering information and minimising mistakes. The whole process is done automatically [34][17]. AI can also be used to identify transactions automatically based on established criteria and previous data patterns which simplifies the process of categorising financial transactions, reducing time while insuring correct financial records [11][18]. This is also helpful to reduce human efforts and to enhance accuracy in transactions. In addition, AI-driven systems make bank reconciliation more efficient; and match statement transactions with matching accounting system entries, facilitating the reconciliation procedure and decreasing inconsistencies [35][19]. AI is also helpful to automate the processing of invoices; validate invoice information, update records, and start payment processing, removing the need for user involvement and accelerating the payment cycle [36][20].
AI automation also facilitates real-time reporting related to financial matters. It automatically generates and provides financial reports available and gives real-time insight for making decisions [37][21]. AI also automates tax calculations, applies the most recent tax regulations, and creates accurate tax reports, minimising the possibility of mistakes in filing taxes and improving tax planning [38,39][22][23]. It has a critical role in identifying fraudulent activity by constantly analysing financial transactions and protecting firms from financial and reputational losses [40][24]. AI predicts future financial patterns, monetary flows, and performance measures, facilitating data-driven financial choices and strategic planning through predictive financial analysis [41][25].
AI-backed automation has enormous advantages in accounting. From performing routine tasks to analyzing and providing data for decision-making, it also saves time and cost, the need for experts, and allows accounting professionals to concentrate on strategic activities. AI-based automation is the need of present-day accounting as the needs of clients and businesses are changing very rapidly. It ensures economic growth by analyzing the data according to the market needs.

3. AI Algorithms and Analysis

Accounting has been profoundly affected by AI algorithms, which have revolutionised old practises and enabled accountants and financial professionals to perform more effectively [42][26]. Machine learning and natural language processing, for example, can alter multiple components of accounting, such as entering data, financial analysis, identifying fraud, and processes for making decisions [43,44][27][28]. With the help of AI algorithms, the extraction of pertinent information from documents such as bills, receipts, and financial statements can be made automated which reduces errors, save time, and improves data accuracy [45][29]. AI algorithms are capable of analysing massive volumes of financial data to identify patterns, trends, and irregularities [46][30]. This helps in more accurate financial analysis and forecasting, allowing firms to make better decisions and detect possible risks and opportunities. AI systems generate alarms when suspicious behaviours are detected by continually analysing transaction patterns and financial data assisting businesses in mitigating fraud risks and inefficiencies [47][31]. It also detects possible non-compliance concerns and gives insights to assist businesses comply with regulatory obligations by monitoring financial activities and data [23][4]. Last but not least AI virtual assistants give real-time help to accountants and customers by answering questions and delivering financial insights on required [48][32]. Accounting AI algorithms offer the ability to expedite operations, enhance accuracy, and give accountants time to concentrate on other responsibilities. As innovation takes place in AI technology and it gets advancements, its incorporation with accounting practises is likely to grow [49][33]. Its applications and benefits will be changing the accounting profession’s future and so accountants and businesses must adopt AI in accounting. It is also necessary to adopt adequate measures regarding the security and privacy of data, training of accountants, etc. for the efficient use of AI algorithms in accounting activities.

4. AI and Accountant’s Efficiency

AI has a significant influence on the efficiency of accountants. AI enables accountants to concentrate on better planning and valuable tasks by automating repetitive processes such as entering data, reconciliation, and report-making [50][34]. It will decrease the requirement for manual labor and enable accountants to concentrate on more value-added operations [51][35]. Furthermore, the ability of AI to handle large volumes of data allows accountants to obtain a greater understanding of financial performance while making decisions based on data. AI-powered technologies may detect inconsistencies, unexpected transactions, and possible fraud, hence improving the quality of financial audits [52][36]. AI-powered predictive analytics also helps accountants with planning and financial forecasting, enabling them to develop realistic budgets and adopt proactive financial plans [53][37].
The capacity of AI to analyse individual customers’ financial data enables accountants to deliver personalised financial advice and solutions, leading to happier customers and improved client-accountant relations [54][38]. Despite these advantages, concerns related to the security of data, human control, and moral issues need to be resolved to ensure that AI is used responsibly and effectively in accounting [29][10]. As dependency on AI-based systems grows, ensuring data privacy and security becomes increasingly vital. Comprehensive security measures are essential to safeguard critical financial data from unauthorised access, among other things. Another critical problem is the ethical difficulties that occur as a result of the use of AI in accounting. Accountants and businesses must take proactive steps to guarantee that AI-powered operations are transparent, fair, and ethical. Furthermore, as AI becomes more integrated into the accounting system, accountants must learn how to connect with AI systems, optimise their use, and assess their outputs.
Accountants’ roles will continue to change as AI evolves, with a higher focus on technological skills, data analysis, and innovative thinking [55][39]. While AI will automate many activities, human accountants will be necessary for AI-generated understandings, making technical judgments, and preserving accounting ethics. Accountants’ collaboration with AI technology provides a future in which accounting is more dynamic, and data-driven [56][40]. Accounting performance is considerably enhanced through AI by automating difficult jobs, improving accuracy, offering real-time insights, accelerating reconciliation procedures, and supporting fraud detection. Accountants may more effectively manage their time and expertise, improving resource utilisation and leading to improved financial results for businesses.

5. AI-Driven Decision and Regulatory Standards

AI has also a positive role in accounting decision-making according to regulatory standards [46][30]. Its innovative capabilities provide several benefits that help accountants and organisations make better financial decisions while complying with regulatory regulations [57][41]. AI improves reliability and accuracy in accounting records by analysing and organising data in real-time, minimising the probability of mistakes in reporting and decision-making [58][42]. As it can analyze huge data, it has also the ability to extract useful and required information for better decisions according to market demands [59][43]. This responsiveness coincides with the regulatory bodies’ requirement for timely and accurate financial reporting. It is important to highlight that accounting decisions should follow regulatory standards for which the role of AI cannot be ignored [60][44]. For example, it improves the procedures of data validation, verification, and reporting and automates these steps that assist accountants in meeting regulatory requirements while reducing errors. Moreover, the pattern and anomaly recognition capabilities of AI help in accounting fraud detection and assists accountants in taking preventative steps for mitigating fraud risks [39][23]. Adherence to fraud prevention rules is critical for sustaining trust and integrity, making AI a significant partner in fraud detection and decision-making. AI-powered systems perform data validation and verification steps in an automated manner and make the audit process simple. This saves auditors time while ensuring transparency and fulfillment of regulatory audit standards, and strengthens the credibility and reliability of financial data to be used in decision-making [61][45]. Furthermore, AI’s predictive analytics plays a vital role in budgeting and forecasting and helps accountants to make effective and efficient data-based projections. This ability is also critical for meeting regulatory planning and reporting obligations, as well as facilitating sound decisions for sustainable financial growth [62][46].
AI considerably enhances accounting decision-making while complying with regulations. Its abilities for data analysis, accuracy, real-time insights, identifying fraud, compliance automation, and ethical decision-making help accelerate monetary operations and assure regulatory compliance. AI enables accountants to handle financial data more effectively, and increase transparency according to the regulations; which contribute to better financial governance and trust among stakeholders [63][47]. As AI advances, its function in accounting decisions will become even more critical in managing a more complicated and regulated financial industry.

References

  1. Agustí, M.A.; Orta-Pérez, M. Big data and artificial intelligence in the fields of accounting and auditing: A bibliometric analysis. Span. J. Financ. Account./Rev. Española Financ. Contab. 2023, 52, 412–438.
  2. Marthen, C. Impact of Artificial Intelligence (AI) Technology on Accounting. SSRN Electron. J. 2023.
  3. Ibrahim, M.; Abdullah, A.; Khairudin, N.; Salleh, M.S.M. Artificial intelligence diffusion among accountants in Malaysian listed companies. In AIP Conference Proceedings; AIP Publishing: Long Island, NY, USA, 2023; p. 020054.
  4. Rahman, M.J.; Zhu, H. Predicting accounting fraud using imbalanced ensemble learning classifiers—Evidence from China. Account. Financ. 2023, 63, 3455–3486.
  5. Crona, B.; Sundström, E. Sweet Spots or Dark Corners? An Environmental Sustainability View of Big Data and Artificial Intelligence in ESG. In Handbook of Big Data and Analytics in Accounting and Auditing; Springer: Singapore, 2023; pp. 105–131.
  6. Alshurafat, H. The Usefulness and Challenges of Chatbots for Accounting Professionals: Application On ChatGPT. SSRN Electron. J. 2023.
  7. Rawashdeh, A.; Bakhit, M.; Al-Okdeh, S. The Mediating Role of Control Risk in the Relationship between Technological Factors and AI-Based Predictive Analytics Adoption: Evidence from Audit Firms in the US. In Proceedings of the 2023 International Conference on Business Analytics for Technology and Security (ICBATS), Dubai, United Arab Emirates, 7–8 March 2023; pp. 1–7.
  8. Prokofieva, M. Integrating data analytics in teaching audit with machine learning and artificial intelligence. Educ. Inf. Technol. 2023, 28, 7317–7353.
  9. Obaydin, I.; Troshani, I.; Zurbruegg, R. AI capability and internal control effectiveness. SSRN Electron. J. 2023.
  10. Zhang, C.; Zhu, W.; Dai, J.; Wu, Y.; Chen, X. Ethical impact of artificial intelligence in managerial accounting. Int. J. Account. Inf. Syst. 2023, 49, 100619.
  11. Jackson, D.; Michelson, G.; Munir, R. Developing accountants for the future: New technology, skills, and the role of stakeholders. Account. Educ. 2023, 32, 150–177.
  12. Ziesche, S.; Agarwal, S.; Nagaraju, U.; Prestes, E.; Singha, N. Role of Artificial Intelligence in Advancing Sustainable Development Goals in the Agriculture Sector. In The Ethics of Artificial Intelligence for the Sustainable Development Goals; Springer: Cham, Switzerland, 2023; pp. 379–397.
  13. Putri, R.; Werastuti, D.N.S.; Astuty, E.D.; Khairunnisa, A.F.; Wahyono, E.; Apriani, N.L. Ni Luh Apriani Integrated Reporting: Corporate Strategy Towards Achieving Sustainable Development SDGs. Apollo J. Tour. Bus. 2023, 1, 64–71.
  14. ISA. What Is Automation? Available online: https://www.isa.org/about-isa/what-is-automation (accessed on 12 September 2023).
  15. Bavaresco, R.S.; Nesi, L.C.; Victória Barbosa, J.L.; Antunes, R.S.; da Rosa Righi, R.; da Costa, C.A.; Vanzin, M.; Dornelles, D.; Junior, S.C.; Gatti, C.; et al. Machine learning-based automation of accounting services: An exploratory case study. Int. J. Account. Inf. Syst. 2023, 49, 100618.
  16. Makarova, E.N.; Skachkova, R.V.; Takhtomysova, D.A.; Fedotova, E.S.; Aukina, A.I. Automation of Accounting and Settlement Operations as a Form of Digital Transformation of the Cooperative Sector of the Economy. In Big Data in Information Society and Digital Economy; Springer: Cham, Switzerland, 2023; pp. 207–213.
  17. Tsoraya, N.D.; Asbari, M.; Novitasari, D. The Role of Accounting Information Systems in the Industrial Revolution 4.0. J. Inf. Syst. Manag. 2022, 2, 44–47.
  18. Han, H.; Shiwakoti, R.K.; Jarvis, R.; Mordi, C.; Botchie, D. Accounting and auditing with blockchain technology and artificial Intelligence: A literature review. Int. J. Account. Inf. Syst. 2023, 48, 100598.
  19. Kumar, A.; Patel, N. The Impact of AI Technology on the Financial Sector and How AI Is Modifying the State of Modern-Day Financial Institutions by Banking 4.0. 2022. Available online: https://www.eurchembull.com/uploads/paper/38e148daa207bf1b60e581bbf7590e6e.pdf (accessed on 3 March 2023).
  20. Ma, K.W.F.; Dhot, T.; Raza, M. Considerations for Using Artificial Intelligence to Manage Authorized Push Payment (APP) Scams. IEEE Eng. Manag. Rev. 2023, 51, 166–179.
  21. Dumitru, V.F.; Ionescu, B.-Ș.; Rîndașu, S.-M.; Barna, L.-E.-L.; Crîjman, A.-M. Implications for Sustainability Accounting and Reporting in the Context of the Automation-Driven Evolution of ERP Systems. Electronics 2023, 12, 1819.
  22. European Union. Directive 2022/2464/EU of the European Parliament and of the Council of 14 December 2022 Amending Regulation (EU) No 537/2014, Directive 2004/109/EC, Directive 2006/43/EC and Directive 2013/34/EU, as Regards Corporate Sustainability Reporting. 2022. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32022L2464&from=EN (accessed on 1 August 2023).
  23. Hu, B.; Wu, Y. AI-based Compliance Automation in Commercial Bank: How the Silicon Valley Bank Provided a Cautionary Tale for Future Integration. Int. Res. Econ. Financ. 2023, 7, 13–15.
  24. Brusseau, J. AI human impact: Toward a model for ethical investing in AI-intensive companies. J. Sustain. Financ. Investig. 2023, 13, 1030–1057.
  25. Schmitt, M. Automated machine learning: AI-driven decision making in business analytics. Intell. Syst. Appl. 2023, 18, 200188.
  26. Zhang, M. Problems and countermeasures of accounting informatization construction in colleges and universities under the background of big data and artificial intelligence. J. Comput. Methods Sci. Eng. 2023, 23, 747–757.
  27. Bochkay, K.; Brown, S.V.; Leone, A.J.; Tucker, J.W. Textual Analysis in Accounting: What’s Next? Contemp. Account. Res. 2023, 40, 765–805.
  28. Duan, H.K.; Vasarhelyi, M.A.; Codesso, M.; Alzamil, Z. Enhancing the government accounting information systems using social media information: An application of text mining and machine learning. Int. J. Account. Inf. Syst. 2023, 48, 100600.
  29. Dandale, M.N.; Mazharunnisa; Daniel, D.J.J.D.; Priya, R.S.; Walid, M.A.A.; Thulasimani, T. Business Process Automation using Robotic Process Automation (RPA) and AI Algorithm’s on Various Tasks. In Proceedings of the 2023 8th International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, 1–3 June 2023; pp. 821–827.
  30. Paurav Thakker, G.J. Emerging Technologies in Accountancy and Finance: A Comprehensive Review. Eur. Econ. Lett. 2023, 13, 993–1011.
  31. Dayyabu, Y.Y.; Arumugam, D.; Balasingam, S. The application of artificial intelligence techniques in credit card fraud detection: A quantitative study. E3S Web Conf. 2023, 389, 07023.
  32. Kamoonpuri, S.Z.; Sengar, A. Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail. J. Retail. Consum. Serv. 2023, 72, 103258.
  33. Cho, S.; Vasarhelyi, M.A.; Sun, T.; Zhang, C. Learning from Machine Learning in Accounting and Assurance. J. Emerg. Technol. Account. 2020, 17, 1–10.
  34. Damerji, H.; Salimi, A. Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting. Account. Educ. 2021, 30, 107–130.
  35. Danimir Gulin, C. Digitalization and the Challenges for the Accounting Profession. Entren.-Enterp. Res. Innov. 2019, 2, 428–437.
  36. Yoon, S. A Study on the Transformation of Accounting Based on New Technologies: Evidence from Korea. Sustainability 2020, 12, 8669.
  37. Kaya, C.T.; Turkyilmaz, M.; Birol, B. RPA Teknolojilerinin Muhasebe Sistemleri Üzerindeki Etkisi. Muhasebe Finans. Derg. 2019, 82, 235–250.
  38. Boustani, N.M. Artificial intelligence impact on banks clients and employees in an Asian developing country. J. Asia Bus. Stud. 2022, 16, 267–278.
  39. Qasim, A.; Kharbat, F.F. Blockchain Technology, Business Data Analytics, and Artificial Intelligence: Use in the Accounting Profession and Ideas for Inclusion into the Accounting Curriculum. J. Emerg. Technol. Account. 2020, 17, 107–117.
  40. Luo, J.; Meng, Q.; Cai, Y. Analysis of the Impact of Artificial Intelligence Application on the Development of Accounting Industry. Open J. Bus. Manag. 2018, 6, 850–856.
  41. Issa, H.; Sun, T.; Vasarhelyi, M.A. Research Ideas for Artificial Intelligence in Auditing: The Formalization of Audit and Workforce Supplementation. J. Emerg. Technol. Account. 2016, 13, 1–20.
  42. Lehner, O.M.; Knoll, C. Artificial Intelligence in Accounting; Routledge: London, UK, 2022.
  43. Hoogendoorn, M. International Accounting Regulation and IFRS Implementation in Europe and Beyond—Experiences with First-time Adoption in Europe. Account. Eur. 2006, 3, 23–26.
  44. Needles, B.E. Accounting Education: The Impact of Globalization. Account. Educ. 2010, 19, 601–605.
  45. Barth, M.E.; Landsman, W.R. How did Financial Reporting Contribute to the Financial Crisis? Eur. Account. Rev. 2010, 19, 399–423.
  46. Kommunuri, J. Artificial intelligence and the changing landscape of accounting: A viewpoint. Pac. Account. Rev. 2022, 34, 585–594.
  47. Morais, A.I. Are changes in international accounting standards making them more complex? Account. Forum 2020, 44, 35–63.
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