Application of artificial intelligence in budget management: a systematic review

Castillo-Oliva J.; Montañez-Díaz B.A.; Mendoza-Rivera R.D. · Aibi, Revista de Investigacion Administracion e Ingenierias (2025) · DOI: 10.15649/2346030x.4199

Resumen

In budget management, traditional methods have been criticized for their rigidity and inefficiency in dynamic environments. This study systematically reviews the applications of artificial intelligence (AI) in organizational budget management. The specific objectives are: (i) to classify the functions of artificial intelligence according to the stages of the budgeting process, (ii) identify the aspects in which artificial intelligence contributes to improving budget management, and (iii) characterize the AI algorithms used according to their technical classification and frequency of application in budget management. The PRISMA methodology was employed, and searches were conducted in Scopus, ScienceDirect, and Wiley, selecting 14 studies. The findings showed that AI is applied in expenditure distribution, financial risk prediction, internal control evaluation, cost budget control, and budget performance evaluation. It improves decision-making, expense control, operational efficiency, and budgetary accuracy. The most commonly used algorithms include Convolutional Neural Networks (CNN), Backpropagation Neural Networks (BPNN), Genetic Algorithms, Multilayer Perceptron, Dynamic Distributed Clustering Algorithm, and Multiple Linear and Logistic Regression models. The research concludes that AI shows evident utility and promising results in budget management. However, it is recommended to delve deeper into its applications in specific budget management functions and explore less studied but relevant areas in financial administration.

Instituciones: Universidad Nacional de Trujillo