Artificial Intelligence and Accounting Research: A Framework and Agenda
November 20, 2025 Β· Declared Dead Β· π International Journal of Accounting Information Systems
"No code URL or promise found in abstract"
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Authors
Theophanis C. Stratopoulos, Victor Xiaoqi Wang
arXiv ID
2511.16055
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CY,
econ.GN
Citations
0
Venue
International Journal of Accounting Information Systems
Last Checked
4 months ago
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.
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