AI正重塑会计研究范式,该文提出分类框架并指导学者定位优势。
Artificial Intelligence and Accounting Research: A Framework and Agenda
- 按研究焦点与方法将会计AI研究分为四类,构建分析框架。
- 揭示人类在理论深度与创意上仍不可替代,但竞争压力显著提升。
- 适合关注AI与会计融合、科研转型的学者参考。
生成式人工智能(GenAI)和大语言模型(LLMs)的快速发展正在深刻改变会计研究,既带来机遇也构成竞争威胁。本文提出一个二维分类框架,从研究焦点(会计中心或AI中心)和方法论(基于AI或传统方法)对相关研究进行划分。通过该框架分析IJAIS特刊及顶级会计期刊中的近期论文,梳理现有研究并识别潜在方向。进一步探讨会计学者如何凭借专业优势进行战略定位与协作,凸显其价值所在。同时,对比人类研究者与AI代理在全研究流程中的能力差异,发现尽管GenAI降低了部分门槛,但对高阶贡献的要求提高,强调了人类判断力、创造力与理论深度的重要性。这要求改革博士教育,培养兼具比较优势与AI素养的研究人才。
原文摘要 · Abstract (English)
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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