In today's rapidly evolving business landscape, organizations must optimize their project portfolios by balancing agility, operational efficiency, and AI-driven resource allocation. Traditional portfolio management methodologies, while structured, often struggle to accommodate real-time market dynamics, resource constraints, and shifting organizational priorities. The integration of Agile, Lean Six Sigma, and AI-augmented decision-making models has transformed strategic portfolio optimization, enabling companies to achieve greater flexibility, efficiency, and data-driven forecasting. This study examines how Agile principles enhance adaptability and iterative value delivery, while Lean Six Sigma methodologies contribute to process efficiency, waste reduction, and continuous improvement. By integrating these frameworks with AI-powered resource allocation models, organizations can leverage predictive analytics, machine learning algorithms, and real-time scenario modeling to optimize project selection, investment distribution, and risk mitigation. Comparative analysis illustrates the synergistic benefits of combining Agile, Lean Six Sigma, and AI-driven portfolio management, highlighting how companies can achieve faster decision-making, enhanced productivity, and more precise resource alignment. Additionally, key challenges, including AI model transparency, change resistance, and the complexity of hybrid implementation, are addressed alongside strategies to foster cross-functional collaboration and leadership buy-in. By aligning strategic business objectives with advanced project execution methodologies, this study presents a comprehensive portfolio optimization framework that enables organizations to maximize return on investment, minimize operational inefficiencies, and enhance responsiveness to dynamic market conditions.