This paper explores the intersection of macroeconomic cycle analysis and artificial intelligence (AI) to propose a transformative approach to economic forecasting and policymaking. Kitchin, Juglar, Kuznets, Schumpeterian, Kondratieff, and Real Business Cycles are all macroeconomic cycles that are necessary to understand economic fluctuations and their effects on stability, employment, and growth. Traditional approaches to analyzing these cycles frequently fail to accurately predict turning points and effectively manage their complexities. AI integration is a powerful solution because it enables real-time monitoring, predictive modeling, and scenario simulation. This paper presents an AI-driven foresight framework designed to improve economic policy decisions using data integration, machine learning models, and decision support systems. Applications are evaluated in a wide range of critical areas, including fiscal planning, monetary policy, labor market management, financial stability, and climate-responsive strategies. AI can improve inflation forecasting, optimize tax policies, and facilitate workforce reskilling, among other benefits, as demonstrated by real-world examples AI can help governments and institutions prevent recessions, reduce inflation, and promote long-term sustainability. This study emphasizes the importance of combining technological innovation with ethical and transparent practices, and it provides a framework for leveraging AI’s potential to build more inclusive and resilient economies.