Artificial intelligence and accounting research: a framework and agenda

Recent advances in artificial intelligence, particularly generative AI and large language models (LLMs), are fundamentally transforming accounting research, creating both unprecedented 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 recent AI-accounting research published in leading accounting journals, including papers from the IJAIS special issue, to map existing studies and identify research opportunities. Using this same framework, we analyze comparative advantages of accounting researchers relative to industry and computer science researchers, identifying strategic opportunities in each quadrant. We further examine how generative AI and LLMs transform the research process itself, comparing capabilities of human researchers and AI agents across the entire research workflow. This analysis reveals that while generative AI democratizes certain research capabilities, it simultaneously intensifies competition by raising expectations for higher-order contributions where human judgment, creativity, and theoretical depth remain irreplaceable. These shifts require reforming doctoral education to cultivate comparative advantages while building AI fluency.