Impact of Artificial Intelligence and the Future of the Accounting Profession
Keywords:
Accounting Profession, Artificial Intelligence (AI), Business Learning (BL), Accounting Software, Automation TechnologyAbstract
This study aims to draw attention to the effects artificial intelligence has had on the accounting industry and the opportunities that this change has created. An essential element of an accountant's job entails the gathering and examination of copious amounts of financial information. The accountant is required to mine these data for nuggets of information that provide insight into the operational and financial aspects of the company. Traditionally, the accountant has been the only person responsible for completing this task, and they have received no outside assistance. However, in today's world, many computer-based tools are accessible to assist in the performance of financial analysis jobs. Artificial intelligence is currently one of the most prominent tools (AI). For example, the phrase "artificial intelligence" (AI) comes from computer science. It refers to a computer's capacity to imitate human cognitive abilities such as learning, evaluating, problem-solving, and decision-making. In accounting, the goal of applying artificial intelligence is to boost productivity in fundamental and necessary procedures and processes in such a way that, in the long run, it results in improved business decisions. This paper aims to understand the impact that Artificial Intelligence solutions have had in accounting over the past few years by performing a qualitative study based on a survey of relevant literature from the past few years. This article highlights the potential changes that Artificial Intelligence can bring to accounting occupations and the required actions to be taken to prepare for future jobs, which will more frequently involve using Artificial Intelligence solutions.
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Achar, S. (2015). Requirement of Cloud Analytics and Distributed Cloud Computing: An Initial Overview. International Journal of Reciprocal Symmetry and Physical Sciences, 2, 12–18. https://upright.pub/index.php/ijrsps/article/view/70
Achar, S. (2016). Software as a Service (SaaS) as Cloud Computing: Security and Risk vs. Technological Complexity. Engineering International, 4(2), 79–88. https://doi.org/10.18034/ei.v4i2.633
Achar, S. (2017). Asthma Patients’ Cloud-Based Health Tracking and Monitoring System in Designed Flashpoint. Malaysian Journal of Medical and Biological Research, 4(2), 159-166. https://doi.org/10.18034/mjmbr.v4i2.648
Achar, S. (2018). Security of Accounting Data in Cloud Computing: A Conceptual Review. Asian Accounting and Auditing Advancement, 9(1), 60–72. https://4ajournal.com/article/view/70
Achar, S. (2019a). Cloud-based System Design. International Journal of All Research Education and Scientific Methods (IJARESM), 7(8), 23-30. http://www.ijaresm.com/cloud-based-system-design
Achar, S. (2019b). Early Consequences Regarding the Impact of Artificial Intelligence on International Trade. American Journal of Trade and Policy, 6(3), 119-126. https://doi.org/10.18034/ajtp.v6i3.634
Adusumalli, H. P., & Pasupuleti, M. B. (2017). Applications and Practices of Big Data for Development. Asian Business Review, 7(3), 111-116. https://doi.org/10.18034/abr.v7i3.597
Chen, S., Deming, C., & Adusumalli, H. P. (2018). Safety Assessment of IoT: Warning Scan for Security. 技术与管理回顾, 1(1), 1–6. Retrieved from https://xn--jhqs8sh4jbvevnt0xk4h3c.xn--6frz82g/index.php/tmr/article/view/1
Fadziso, T., Adusumalli, H. P., & Pasupuleti, M. B. (2018). Cloud of Things and Interworking IoT Platform: Strategy and Execution Overviews. Asian Journal of Applied Science and Engineering, 7, 85–92. https://upright.pub/index.php/ajase/article/view/63
Ganapathy, A. (2016). Blockchain Technology Use on Transactions of Crypto Currency with Machinery & Electronic Goods. American Journal of Trade and Policy, 3(3), 115-120. https://doi.org/10.18034/ajtp.v3i3.552
Ganapathy, A., & Neogy, T. K. (2017). Artificial Intelligence Price Emulator: A Study on Cryptocurrency. Global Disclosure of Economics and Business, 6(2), 115-122. https://doi.org/10.18034/gdeb.v6i2.558
Koehler, S., & Pasupuleti, M. B. (2020). Research on the Court Decide: The Implications of Artificial Intelligence. 技术与管理回顾, 3(1), 1–14. https://xn--jhqs8sh4jbvevnt0xk4h3c.xn--6frz82g/index.php/tmr/article/view/2
Manavalan, M., & Ganapathy, A. (2014). Reinforcement Learning in Robotics. Engineering International, 2(2), 113-124. https://doi.org/10.18034/ei.v2i2.572
Pasupuleti, M. B. (2015). Stimulating Statistics in the Epoch of Data-Driven Innovations and Data Science. Asian Journal of Applied Science and Engineering, 4, 251–254. https://upright.pub/index.php/ajase/article/view/55
Pasupuleti, M. B. (2016). Data Scientist Careers: Applied Orientation for the Beginners. Global Disclosure of Economics and Business, 5(2), 125-132. https://doi.org/10.18034/gdeb.v5i2.617
Pasupuleti, M. B., Miah, M. S., & Adusumalli, H. P. (2019). IoT for Future Technology Augmentation: A Radical Approach. Engineering International, 7(2), 105-116. https://doi.org/10.18034/ei.v7i2.601
Thota, A., Tilak, P., Ahluwalia, S., Lohia, N. (2018). Fake news detection: a deep learning approach. SMU Data Science Review, 1(3). https://scholar.smu.edu/datasciencereview/vol1/iss3/10/
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