Artificial Intelligence and the Future of Accounting: A Systematic Literature Review and Thematic Analysis

Description

This dataset contains the full list of studies reviewed and the thematic coding matrix supporting the systematic literature review "Artificial Intelligence and the Future of Accounting." It maps eight thematic domains (core AI technologies, auditing, financial reporting, forensic accounting, generative AI, education, ethics/governance, and emerging-economy adoption) to representative studies and key findings, covering literature from 2015–2026. Keywords: Artificial Intelligence; Accounting; Systematic Literature Review; Auditing; Fraud Detection

Steps to reproduce

Searched the databases Scopus, Web of Science, ScienceDirect, SpringerLink, IEEE Xplore, and Google Scholar using Boolean combinations of accounting-related keywords (accounting, auditing, financial reporting, forensic accounting, management accounting, tax) and AI-related keywords (artificial intelligence, machine learning, deep learning, RPA, natural language processing, generative AI, large language models). Restricted results to peer-reviewed journal articles and indexed conference proceedings published in English between 2015 and 2026. Screened studies for relevance, including only those primarily addressing accounting/auditing practice, education, or regulation, and excluding studies focused solely on computer science methods with no accounting application. Inductively coded the included studies into themes, then merged them into 8 thematic domains (see Thematic_Synthesis sheet). Cross-validated findings against existing systematic and bibliometric reviews in the field to synthesize the results into the thematic framework presented in the paper

Institutions

• Aqaba University of Technology

  Aqaba, Aqaba

Categories

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