Research on Innovative Pathways for Empowering Corporate Financial Management with Generative Artificial Intelligence

Abstract

With the rapid advancement of digital transformation and artificial intelligence technologies, generative artificial intelligence (Generative AI) has shown broad application prospects in the domain of corporate management. Based on the Technology–Organization–Environment (TOE) theoretical framework and value-chain reengineering theory, this paper constructs an optimized model for empowering corporate financial management with Generative AI. First, it analyzes the core capabilities of generative models in data synthesis, text comprehension, and decision support, and explores innovative pathways for multi-scenario automatic budget preparation, dynamic financial forecasting, and automated compliance audit report generation within the contexts of corporate budgeting, predictive analysis, and risk control. Second, it proposes implementation strategies—such as organizational restructuring, enhancement of data-governance systems, and establishment of continuous iteration mechanisms—and, drawing on representative enterprise case studies, demonstrates how Generative AI improves forecast accuracy, optimizes risk alerts, and enhances audit efficiency. Finally, it addresses challenges related to model bias, data-privacy protection, computational resource investment, and algorithmic transparency, offering technical improvements and governance measures to guide enterprises in deploying Generative AI applications under compliance and ethical constraints. The study shows that Generative AI not only elevates the intelligence level of financial management but also drives enterprise value creation and sustained innovation through dynamic decision support.