Futures Studies on Artificial Intelligence in Management Accounting

The present study was conducted with the aim of exploring the future applications of artificial intelligence (AI) in management accounting and is applied and descriptive (non-experimental) in nature. Data collection was carried out using a mixed-methods approach, combining field and library research techniques. The tools employed included expert panels, semi-structured interviews, open-ended questionnaires, the fuzzy Delphi method, observation, and document analysis. The statistical population consisted of professors, doctoral students, members of the Management Accountants Association, and professional specialists in this field in Iran. Sampling was performed using theoretical and snowball methods, and interviews continued until theoretical saturation was reached. Data analysis was conducted both qualitatively and quantitatively, leading to the identification of key drivers in management accounting education and research. Based on the results of the fuzzy Delphi analysis, the technology of deep learning ranked first with a fuzzy mean of ۳.۷ and was recognized as the most critical driver. Subsequently, natural language processing (NLP) with a mean of ۳.۴ was also identified among the accepted technologies. Blockchain technology, with a score of ۳.۱, was evaluated as conditional and requires further investigation. Additionally, explainable artificial intelligence (XAI) was proposed as an emerging driver that could play a significant role in enhancing transparency, trust, and regulatory compliance. The findings of this research indicate that the future of management accounting will be directly influenced by technological advancements in AI. To leverage these technologies effectively, strategic planning and investments in education and infrastructure development are essential. The present study was conducted with the aim of exploring the future applications of artificial intelligence (AI) in management accounting and is applied and descriptive (non-experimental) in nature. Data collection was carried out using a mixed-methods approach, combining field and library research techniques. The tools employed included expert panels, semi-structured interviews, open-ended questionnaires, the fuzzy Delphi method, observation, and document analysis. The statistical population consisted of professors, doctoral students, members of the Management Accountants Association, and professional specialists in this field in Iran. Sampling was performed using theoretical and snowball methods, and interviews continued until theoretical saturation was reached. Data analysis was conducted both qualitatively and quantitatively, leading to the identification of key drivers in management accounting education and research. Based on the results of the fuzzy Delphi analysis, the technology of deep learning ranked first with a fuzzy mean of ۳.۷ and was recognized as the most critical driver. Subsequently, natural language processing (NLP) with a mean of ۳.۴ was also identified among the accepted technologies. Blockchain technology, with a score of ۳.۱, was evaluated as conditional and requires further investigation. Additionally, explainable artificial intelligence (XAI) was proposed as an emerging driver that could play a significant role in enhancing transparency, trust, and regulatory compliance. The findings of this research indicate that the future of management accounting will be directly influenced by technological advancements in AI. To leverage these technologies effectively, strategic planning and investments in education and infrastructure development are essential.

کلیدواژه ها:

Futures studies on artificial intelligence ، management accounting ، deep learning ، natural language processing ، blockchain