ABSTRACT: Accounting is at a turning point as AI moves from rule-based automation to generative systems, and this review asks what the field has become, where it is credibly headed. We assemble a PRISMA-guided bibliometric map of 174 Scopus-indexed, AJG-listed journal articles from 2000 to 2025, using Biblioshiny and VOSviewer to follow production and citation dynamics, keyword co-occurrences, thematic evolution, and collaboration networks across authors, institutions, and countries. The trajectory is unmistakable: research accelerates in the 2020s (18.13% annual growth since 2020), with output roughly tripling after the diffusion of large language models. The domain organizes around four cohesive clusters, core AI techniques (machine learning, deep learning, RPA, big data), accounting functions (financial reporting, auditing, management control), human–professional themes (skills, ethics, education), and emergent technologies (LLMs, autonomous agents, blockchain/fintech), while collaboration remains polycentric yet weakly bridged, with international co-authorship still limited at 28.74%. Conceptually, the center of gravity shifts from automating tasks to enabling generative cognition, repositioning accountants toward interpretation, governance, and assurance of AI systems and pushing curricula, explainability norms, and organizational governance to the foreground. Unlike earlier reviews that are largely pre-LLM, descriptive, or method-siloed, our analysis dates inflection points, recenters LLMs and autonomous agents as the organizing core of today’s map and connects science-mapping to normative debates on legitimacy, stewardship, and accountability to yield decision-grade implications for educators, firms, and regulators. The evidence base is necessarily bounded, drawn from Scopus, limited to English AJG outlets, and excluding grey literature, and emergent topics suffer from partial 2025 indexing, novelty effects that depress citations and density, and volatile keywords that can blur short-window patterns; within those bounds, the field’s direction is clear: a shift from automation to accountable intelligence.
KEYWORDS: Artificial intelligence; Accounting; Bibliometric analysis; Large language models; Audit automation.
