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Artificial Intelligence Implementation in Accounting Processes

The article by Bakarich and O’Brien (2021) refers to the problem of the implementation of AI technologies in the field of accounting. The most popular technologies in this sphere are machine learning (ML) and robotic process automation (RPA) (Bakarich & O’Brien, 2021). The research aims to determine to which extent these artificial intelligence technologies are applied now and are expected to be applied in five years. Artificial intelligence seems to be a prospective technology, and its implementation in accounting processes is inevitable.

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The article includes some quantitative and qualitative research based on the secondary data concerning the issue of AI in the field of accounting. The analysis provided in the article is based on the answers of 90 participants from different positions and service lines. According to the research, the accountants estimate the application of the AI in the audit, tax, and advisory fields. Two options are considered: robotic process automation and machine learning. Robotic process automation allows replacing and labor-intensive tasks of integrating the IT-systems (Bakarich & O’Brien, 2021). Besides, robotic systems are able to calculate tax books, evaluate discrete code or transactions, and to complete tax return workbooks. Machine learning technologies allow pulling essential data from lease contracts, analyzing large amounts of information, extracting the information from legal documents. These tasks can be implemented due to pattern recognition, and it simplifies data processing. Thus, artificial intelligence can successfully perform a range of tax, advisory, or audit functions.

The progress in the field of AI development can disrupt the advisory or consulting service lines. The employees have to be shifted to the positions demanding more complex and value-added analysis for the clients (Bakarich & O’Brien, 2021). Thus, the professionals should be ready for acquiring some new skills in order to adapt to the changing environment. Despite the fact that many operations are going to be automated, human operators will remain an important part of the business processes.

The article also provides a quantitative analysis of the extent to which the AI is implemented in the companies. The respondents of the survey had to estimate it by answering a range of questions. For example, they had to estimate their level of expertise with some artificial intelligence technologies. The number of trainings on the AI provided by the company was considered as well as the ability of clients to work with AI. The frequency of utilizing the AI during performing accounted tasks was also among the important factors for the analysis. The results of the research revealed that the most important factor that determines the level of AI implementation is the firm size. Such factors as expertise, perception, training, client usage, adoption seem to have no significant difference. The position of the respondent also influenced the level of self-estimated level of expertise in the field of AI.

All in all, the qualitative responses confirm the quantitative analysis. More than half of the respondents answered that the AI technologies are surely going to become the essential part of accounting processes in the coming years. The views of the respondents are mostly optimistic, although several respondents have indicated such negative points as employee pushback, increased costs, and lack of focus strategies on AI implementation. One of the key conclusions is that despite the respondents believe that the AI technologies are going to develop greatly within five years, nowadays the AI is not extensively used by accountants. Practitioners should consider the strategies that would encourage the adoption of AI in companies.

Reference

Bakarich, K. M., & O’Brien, P. E. (2021). The Robots are Coming… But Aren’t Here Yet: The Use of Artificial Intelligence Technologies in the Public Accounting Profession. Journal of Emerging Technologies in Accounting, 18(1), 27–43. Web.

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