From Risk to Resilience: How Artificial Intelligence Transforms Internal Control Systems for Sustainability

Abstract

Purpose

This study aims to examine the publishing trends on how artificial intelligence transforms internal control system for sustainability. Moreover, this paper explores the relationship between the research constituents using science mapping techniques and the role of artificial intelligence in transforming internal control systems.

Design/Methodology/Approach

Data has been extracted from the Scopus database using a bibliometric approach. To gather pertinent information, a comprehensive search strategy was designed. Data analysis has been performed using Excel, Bibliometric R studio biblioshiny package.

Findings

The findings of this study indicate a growing academic interest in research on Artificial Intelligence and internal control systems over the past few years. It also helps to understand about sustainable practices by integrating artificial intelligence with internal control system.

Research limitations/implications

The reliance on a single database for literature retrieval may limit the study's comprehensiveness, as some relevant studies may not be indexed in this database.

Practical implications

The qualitative insights generated by this study will empower education administrators to make data-driven decisions.

Originality/value

This study provides a comprehensive review of the current research landscape on AI in Internal Control System, identifying knowledge gaps and outlining a future research agenda to advance the field.