Between mirrors and walls: symbolic disputes and algorithmic reconfiguration in accounting

Abstract

Abstract This theoretical essay examines how the diffusion of artificial intelligence (AI) may reconfigure the epistemic and institutional boundaries of accounting under specific conditions of data, governance, and academic incentives. Drawing on a critical review, thematic analysis, and integrative synthesis, it connects classic and recent literature across four axes: the sociology of scientific fields, philosophy of science, the psychodynamics of work, and AI applications in auditing, financial reporting, and tax classification. Four propositions are advanced: (1) AI expansion tends to reward hybrid research that integrates substantive theory, interdisciplinary design, and out-of-sample validation; (2) programs combining accounting and data science may expand institutional impact while facing legitimation barriers; (3) models that are robust to automated validation tend to gain recognition when supported by transparency, substantive interpretation, and governance; and (4) algorithmic ubiquity may strain paradigm fragmentation when institutional incentives foster interdisciplinary co-authorship. Early adoption experiences suggest context-specific operational gains, while regulators and recent research emphasize transparency, bias auditing, and data documentation. The essay concludes that accounting is called to shift from a logic of walls to a logic of bridges, aligning symbolic capital with practical relevance, methodological pluralism, and social responsibility.