BIG DATA, ARTIFICIAL INTELLIGENCE, AND MANAGEMENT ACCOUNTANT: A GLOBAL PERSPECTIVE

Authors

  • Suham Cahyono Universitas Airlangga
  • Ardianto Ardianto Universitas Airlangga

DOI:

https://doi.org/10.34208/jba.v26i1.2081

Keywords:

Accountant Management, Big Data, Artificial Intellegence, Conceptual Framework, Governance

Abstract

This study aims to objectively explored the relevance of big data issues that have developed in the professional world to the best practices of the management accounting profession. The conceptual framework was developed to become the frame for consideration of making structured designs on artificial intelligence issues. Using data sources derived from literature studies and conducting various reviews of articles related to this interesting topic, conclusions are generated that refer to the implications of management accountant best practices. This study finds that the concept of management accountants is strongly influenced by the adoption of Big Data in the companies. Furthermore, we specifically define and present strategic steps that can suggest management accountants can carry out best practices in accordance with professional programs that have become an important part of practice. This study contributes to the development of the best practice of management accountants where Big Data is the center of attention that cannot be separated from their professional practice so that it is possible to adjust the practice of management accountants that generate added value. To the best authors knowledge, this is the first study to seeks and explores the Big Data and Artificial Intellegence in the management accountant profession from global perspectives. The study provides some deep insight to the accountant management global more take care for their sustainable profession in the long wave of digitalisation.

Published

2024-07-23

How to Cite

Cahyono, Suham, and Ardianto Ardianto. 2024. “BIG DATA, ARTIFICIAL INTELLIGENCE, AND MANAGEMENT ACCOUNTANT: A GLOBAL PERSPECTIVE”. Jurnal Bisnis Dan Akuntansi 26 (1):1-16. https://doi.org/10.34208/jba.v26i1.2081.