Predictive Budgeting and Planning with AI in Oracle EPM: Automating Financial Projections

Abstract

The integration of Artificial Intelligence (AI) into financial planning processes has revolutionized traditional budgeting and forecasting methodologies. This paper delves into the application of AI-driven predictive models within Oracle's Enterprise Planning and Budgeting Cloud Service (EPBCS) to automate financial projections, thereby fostering dynamic and adaptive budgeting frameworks. Through a comprehensive analysis, we contrast traditional budgeting approaches with AI-enhanced methods, explore the core functionalities and limitations of EPBCS, and examine the implementation of AI-powered predictive models. We also address the challenges associated with AI adoption in financial planning and propose best practices for seamless integration. Our findings suggest that while AI integration offers substantial improvements in forecasting accuracy and operational efficiency, careful consideration of data governance, model interpretability, and compliance is imperative for successful implementation.