Article: AI-driven management information system for cost accounting and budget optimisation Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.44 pp.75 - 90 Abstract: This study aims to enhance traditional management accounting by developing an AI-based system for cost accounting and budget optimisation. The proposed framework follows a structured nine-step process, beginning with problem identification and concluding with system validation. Each stage ensures transparency and effective implementation. AI contributes to improved prediction accuracy, cost reduction, and more reliable financial decision-making, while highlighting the limitations of outdated, paper-based methods. In practice, AI assists in tasks such as tax processing, error detection, and forecasting. Historical data are used to train AI models, which are then applied to accounting operations and validated for accuracy and relevance. Despite challenges in integration, scalability, and ethical considerations, results indicate strong reliability, with Cronbach's alpha and composite reliability values exceeding 0.8 in SEM tests. Overall, the AI model outperformed traditional methods by reducing costs and adapting effectively to workload variations. Inderscience Publishers - linking academia, business and industry through research

Title: AI-driven management information system for cost accounting and budget optimisation

Authors: Xinying Lu

Addresses: School of Business, Chongqing College of Humanities, Science & Technology, Chongqing, 401524, China

Abstract: This study aims to enhance traditional management accounting by developing an AI-based system for cost accounting and budget optimisation. The proposed framework follows a structured nine-step process, beginning with problem identification and concluding with system validation. Each stage ensures transparency and effective implementation. AI contributes to improved prediction accuracy, cost reduction, and more reliable financial decision-making, while highlighting the limitations of outdated, paper-based methods. In practice, AI assists in tasks such as tax processing, error detection, and forecasting. Historical data are used to train AI models, which are then applied to accounting operations and validated for accuracy and relevance. Despite challenges in integration, scalability, and ethical considerations, results indicate strong reliability, with Cronbach's alpha and composite reliability values exceeding 0.8 in SEM tests. Overall, the AI model outperformed traditional methods by reducing costs and adapting effectively to workload variations.

Keywords: AI-driven; management information system; MIS; cost accounting; budget optimisation; machine learning; decision support systems; financial management; predictive analytics; reinforcement learning; digital transformation.

DOI: 10.1504/IJICT.2025.150405

International Journal of Information and Communication Technology, 2025 Vol.26 No.44, pp.75 - 90

Received: 23 Sep 2025
Accepted: 05 Oct 2025
Published online: 12 Dec 2025 *

Title: AI-driven management information system for cost accounting and budget optimisation

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