BUDGETARY CONTROL AND SALES FORECASTING: AN INTEGRATED APPROACH WITH ARTIFICIAL INTELLIGENCE WITH EMPHASIS ON THE CHILEAN CONTEXT
DOI:
https://doi.org/10.22370/riace.2026.15.1.5837Keywords:
Budgetary control, sales forecasting, artificial intelligence, variance analysis, Chilean contextAbstract
This paper analyzes the role of sales forecasting as a central component of the budgeting process and its impact on management control in dynamic economic environments. From a theoretical-applied approach, it proposes a conceptual model that integrates forecasting in real terms, variance decomposition, and the incorporation of artificial intelligence tools. The study is based on a review of specialized literature in management accounting and forecasting models, using the Chilean context as a reference for application. In this framework, the economic conditions influencing demand estimation are examined, and the opportunities and challenges associated with the adoption of artificial intelligence in organizational settings are discussed. The findings suggest that integrating traditional approaches with machine learning techniques improves predictive accuracy, strengthens variance analysis, and supports the development of more dynamic and adaptive budgeting systems. Furthermore, in economies such as Chile, characterized by high volatility and data availability, artificial intelligence emerges as a relevant tool for strategic decision-making. This approach contributes to strengthening decision-making in organizational contexts characterized by high uncertainty.
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