Assessing the potential integration of large language models in accounting practices: evidence from an emerging economy

Abstract

Abstract This research intends to demonstrate the potential integration of large language models (LLMs) in accounting practices in Jordan. It is a mixed methods study that employs semi-structured interviews and content analysis of published financial reports. A total of 13 semi-structured interviews are conducted with various accounting professionals, such as accountant, financial analyst, financial controller, auditor, tax consultant, and finance manager. In addition, the study includes a thorough content analysis of financial reports, which reveals a compelling pattern highlighting the distinct narrative content richness prevalent across financial, industrial, and service sectors. The results emphasize the need for sector-specific adaptation, suggesting a paradigm shift in financial reporting practices. This study represents the initial empirical exploration in Jordan. It serves as a bridge between theory and application, offering both theoretical insights and practical guidance for accounting professionals. Ultimately, the study envisions a future where LLMs significantly enrich financial reporting practices across diverse sectors.

Keywords

• Accounting practices
• Accounting professionals
• Artificial intelligence
• ChatGPT
• Jordan
• Large language models