Designing an Ethical Framework for the Use of Artificial Intelligence in Accounting and Financial Management with Emphasis on Transparency, Responsibility, and Algorithmic Bias
Keywords:
Artificial intelligence, professional ethics, accounting, financial management, algorithmic transparency, accountability, algorithmic biasAbstract
This study aimed to design an ethical framework for the responsible use of artificial intelligence in accounting and financial management, focusing on algorithmic transparency, professional accountability, and algorithmic bias control. This qualitative study was conducted using thematic analysis. The research population consisted of financial managers, senior accountants, internal auditors, financial technology specialists, and artificial intelligence consultants working in financial organizations and companies located in Tehran. Participants were selected through purposive sampling based on their direct or managerial experience with artificial intelligence systems, financial data analytics, digital accounting, or algorithm-based financial decision-making. Data were collected through semi-structured interviews, and sampling continued until theoretical saturation was achieved. A total of 21 interviews were conducted; theoretical saturation was reached at the eighteenth interview, followed by three additional interviews to ensure data adequacy. After transcription, the data were analyzed using NVivo software through open, axial, and selective coding. The findings revealed that the ethical framework for using artificial intelligence in accounting and financial management consists of five main categories: algorithmic transparency and explainability, professional responsibility and accountability, data fairness and algorithmic bias control, security and confidentiality of financial data, and institutionalization of ethical culture and human oversight. Participants emphasized that the value of artificial intelligence in finance is not limited to prediction accuracy or processing speed; rather, its professional legitimacy depends on explainability, decision traceability, identification of final responsibility, evaluation of data quality, and prevention of the reproduction of historical bias in algorithmic models. The findings suggest that the ethical use of artificial intelligence in accounting and financial management requires a transition from a purely technological perspective to a governance-oriented, human-centered, and accountable approach. The proposed framework can help organizations institutionalize transparency, responsibility, fairness, data security, and human oversight throughout the life cycle of financial AI systems.
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