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

Abstract

This theoretical essay examines how the diffusion of artificial intelligence (AI) may reconfigure the epistemic and institutional boundaries of accounting science 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 diffusion tends to reward hybrid research that integrates substantive theory, interdisciplinary design, and out-of-sample validation; (2) programmes combining accounting and data science may expand institutional impact while facing legitimation barriers; (3) models that withstand automated validation tend to gain recognition when supported by transparency, substantive interpretation, and governance; and (4) algorithmic ubiquity may challenge paradigm fragmentation when institutional incentives support interdisciplinary co-authorship. Early adoption experiences suggest context-specific operational gains, while regulators and recent research emphasize transparency, bias audits, and data documentation. The essay concludes that accounting is called to move from a wall logic to a bridge logic, aligning symbolic capital with practical relevance, methodological pluralism, and social responsibility.