Sztuczna inteligencja w rachunkowości: przegląd bibliometryczny i ewolucja tematyczna z dekady na dekadę
Artificial Intelligence in accounting: A corpus-wide bibliometric review and decade-by-decade thematic evolution

Summary/Abstract: Purpose: This paper aims to map the evolution of artificial intelligence (AI) in accounting research through a corpus-wide and decade-based thematic analysis. We identify dominant themes, key contributors, recent research hotspots, and chart future research trajectories that link historical shifts to emerging priorities. Methodology/approach: We conducted a bibliometric analysis of a SCOPUS dataset (1984–2024). Using a PRISMA screening protocol, 2,863 records were reduced to 451 peer-reviewed articles, followed by thematic synthesis and network mapping in VOSviewer. Findings: Research accelerates sharply after 2015, paralleling advances in machine learning and data availability. The analysis identified four thematic clusters: (1) financial analysis and decision support; (2) regulatory and strategic implications; (3) education and professional adaptation; and (4) digital transformation of accounting information systems. Thematic evolution progresses from early expert systems toward dense, multidisciplinary data-driven ecosystems. Hotspots between 2020 and 2024 include generative AI, automated sustainability reporting, blockchain applications, and predictive analytics, with implications for reporting accuracy, compliance, automation, and skills. Research limitations/implications: Reliance on a single database (SCOPUS) may exclude relevant studies, while PRISMA-based screening and eligibility decisions introduce subjectivity in coverage. Practical implications: The findings are relevant for regulators, educators, and practitioners by outlining emerging themes, governance/ethics, and competency implications. Originality/value: This research delivers an up-to-date, corpus-wide, decade-resolved map that offers a consolidated baseline and practical roadmap for future research and expectations in AI-based accounting.

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