Research on the Application of Artificial Intelligence Technology in Instructional Budget Management

Abstract

Confronted with the increasing dynamism and complexity of educational and teaching activities, the traditional budget management model faces significant challenges in terms of accuracy, foresight, and responsiveness. The development of Artificial Intelligence technology provides a critical pathway for paradigm innovation in instructional budget management. This study systematically explores the application of Artificial Intelligence technology in instructional budget management. Firstly, it constructs an intelligent theoretical framework integrating modern budget theory, data science, and management decision science, analyzing three enabling mechanisms-data-driven processes, workflow reconstruction, and decision augmentation-and designs a hierarchical, decoupled system architecture. Subsequently, the study elaborates on the intelligent application pathways for key stages such as budget formulation, execution monitoring, and performance evaluation, elucidating the shift of management processes toward real-time, precise, and proactive prediction under data-driven approaches. Finally, the research anticipates future trends, including the deepening of human-machine collaboration, the evolution of decision-making models toward predictive and prescriptive modes, and the development of system platforms toward ecosystem-based and self-adaptive directions. This study aims to provide theoretical reference and application guidance for educational institutions in constructing intelligent budget management systems.