Artificial intelligence and accounting research: a framework and agenda

Recent advances in artificial intelligence, particularly generative AI (GenAI) and large language models (LLMs), are fundamentally transforming accounting research, creating both opportunities and competitive threats for scholars. This paper proposes a framework that classifies AI-accounting research along two dimensions: research focus (accounting-centric versus AI-centric) and methodological approach (AI-based versus traditional methods). We apply this framework to papers from the IJAIS special issue and recent AI-accounting research published in leading accounting journals to map existing studies and identify research opportunities. Using this same framework, we analyze how accounting researchers can leverage their expertise through strategic positioning and collaboration, revealing where accounting scholars’ strengths create the most value. We further examine how GenAI and LLMs transform the research process itself, comparing the capabilities of human researchers and AI agents across the entire research workflow. This analysis reveals that while GenAI democratizes certain research capabilities, it simultaneously intensifies competition by raising expectations for higher-order contributions where human judgment, creativity, and theoretical depth remain valuable. These shifts call for reforming doctoral education to cultivate comparative advantages while building AI fluency.

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Publication Details

Journal
International Journal of Accounting Information Systems
Published
2025-11-20
DOI
https://doi.org/10.1016/j.accinf.2025.100760
Citations
4
Primary Topic
Accounting Education and Careers
Type
article
Field-Weighted Citation Impact
15.64
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article

Artificial intelligence and accounting research: a framework and agenda

Victor Xiaoqi Wang, Theophanis C. Stratopoulos
4 citations
International Journal of Accounting Information Systems
Accounting Education and Careers
15.64
article

Artificial intelligence and accounting research: a framework and agenda

Victor Xiaoqi Wang, Theophanis C. Stratopoulos
article en
4 citations

Abstract

Recent advances in artificial intelligence, particularly generative AI (GenAI) and large language models (LLMs), are fundamentally transforming accounting research, creating both opportunities and competitive threats for scholars. This paper proposes a framework that classifies AI-accounting research along two dimensions: research focus (accounting-centric versus AI-centric) and methodological approach (AI-based versus traditional methods). We apply this framework to papers from the IJAIS special issue and recent AI-accounting research published in leading accounting journals to map existing studies and identify research opportunities. Using this same framework, we analyze how accounting researchers can leverage their expertise through strategic positioning and collaboration, revealing where accounting scholars’ strengths create the most value. We further examine how GenAI and LLMs transform the research process itself, comparing the capabilities of human researchers and AI agents across the entire research workflow. This analysis reveals that while GenAI democratizes certain research capabilities, it simultaneously intensifies competition by raising expectations for higher-order contributions where human judgment, creativity, and theoretical depth remain valuable. These shifts call for reforming doctoral education to cultivate comparative advantages while building AI fluency.

International Journal of Accounting Information SystemsVol. 56
University of Waterloo (CA), California State University, Long Beach (US)
Openalex Percentile: Top 1%
Accounting Education and Careers
15.64
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