AI-Assisted Budgeting and Cost Control: A Practical Model for Financial Decision-Making in SMEs

Abstract

In an increasingly uncertain and competitive business environment, effective budgeting and cost control are critical to the financial sustainability of small and medium-sized enterprises (SMEs). However, traditional budgeting practices in SMEs are often constrained by static planning methods, fragmented data, and heavy reliance on managerial intuition. The rapid development of artificial intelligence (AI) offers new opportunities to enhance financial decision-making through data-driven analysis and predictive capabilities. This paper proposes a practical model for AI-assisted budgeting and cost control tailored to the organizational characteristics and resource constraints of SMEs. Adopting a conceptual and application-oriented approach, the study analyzes how AI can support key financial management processes, including budget forecasting, cost monitoring, and decision support, without focusing on technical algorithms or empirical testing. The proposed model emphasizes data integration, continuous analysis, and human-AI collaboration, positioning AI as a tool that augments managerial judgment rather than replacing it. By illustrating key application scenarios and discussing implementation conditions and potential risks, this paper demonstrates how AI-assisted budgeting and cost control can improve flexibility, transparency, and decision quality in SMEs. The study contributes to the understanding of AI-enabled financial management by offering a scalable and managerially relevant framework that supports more adaptive and informed financial decision-making.