Economic policy optimization powered by advanced AI-driven business intelligence tools

Economic policy optimization requires accurate forecasting and data- driven decisionmaking to navigate complex financial situations. This research combines predictive analytics and machine learning models to analyse historical economic data and project future trends using AI- driven economic forecasting. The suggested approach uses time series models (ARIMA, LSTMs) and ensemble learning techniques to increase the accuracy of macroeconomic forecasts, including GDP growth, inflation rates, and labor market dynamics. Additionally, AI- powered models process real- time economic indicators and dynamically adjust policy recommendations in response to global market fluctuations. This approach improves fiscal stability and reduces financial uncertainty by facilitating proactive economic planning. By integrating AI- driven projections into Business Intelligence (BI) dashboards, which provide decision- makers with interactive, real- time information, the efficacy of economic strategies is further enhanced. In order to ensure data- driven governance in a global economy that is always evolving.