From Black Box to Strategic Trust: The Theoretical Synthesis in Strategic Accounting

Abstract

The application of Artificial Intelligence (AI) in strategic accounting has transformed the role of accounting systems from financial reporting to supporting strategic decision-making within organizations. However, the use of AI raises challenges regarding transparency, outcome explanatory capability accountability, and data reliability, which traditional strategic accounting theories cannot fully address. Therefore, there is a need to synthesize knowledge and conceptual frameworks appropriate to the context of accounting in the AI ​​era.

This academic article aims to (1) describe the developmental sequence of concepts and theories related to strategic accounting in the AI ​​era, (2) analyze the strengths, limitations, and connections of related theories, and (3) synthesize theoretical lessons to develop practical application guidelines, using an integrated theoretical synthesis from agency theory, stakeholder theory, legitimacy theory, institutional theory, resource and capability perspective, socio-technological system perspective, and concepts of accountability and auditing. The synthesis reveals that explaining the role of strategic accounting in the AI ​​era requires the integration of multiple theories, as traditional theories have limitations in addressing issues of transparency, the explanatory capability of algorithms, and stakeholder trust. Furthermore, it leads to the proposal of an integrated conceptual framework that links data capability, AI explanatory capability, governance mechanisms, and stakeholder trust to organizational strategic outcomes. This article expands our understanding of strategic accounting in the digital age, provides a conceptual framework for future empirical research, and offers guidance for administrators and policymakers in designing accounting systems that are transparent, auditable, and build stakeholder confidence.