Abstract

This research explores the relationship between Accounting Information Systems (AIS) and risk management in organizational activities, with a focus on the role of autonomous intelligence systems (AIS) in identifying, analyzing, and managing internal and external risks. A demographic analysis of 299 valid participants—balanced in gender and education levels—highlighted that most respondents held degrees, while some had diplomas. The regression analysis, using risk management (RM) and risk assessment (RA) as predictors for AIS Risk Index (AISRI), revealed a lack of model fit, explaining only 1.1% of data variability. The low explanatory power was confirmed by the analysis of variance (ANOVA), indicating the need for a more comprehensive understanding of AISRI. These findings suggest that RM and RA alone are insufficient for accurately predicting AIS effectiveness in risk management. To enhance predictive accuracy, future research should adopt advanced statistical techniques and incorporate a broader range of demographic and contextual variables. This approach would provide a deeper understanding of AISRI and its applications. Moreover, the study underscores the importance of considering practical implications and adopting a nuanced perspective rather than relying solely on RM or RA in AIS-focused risk management.