AI-driven factor-based forex portfolio selection enhances trading strategies by identifying key market drivers that influence currency movements. Using machine learning algorithms, AI analyzes macroeconomic indicators, interest rate differentials, inflation rates, and geopolitical events to determine the most impactful factors affecting forex pairs. AI-driven factor models assess momentum, carry trade opportunities, value metrics, and volatility patterns, enabling traders to build optimized forex portfolios. AI-powered regression analysis and deep learning models evaluate historical data to rank currency pairs based on their expected performance. By integrating risk-adjusted factor weighting, AI ensures that forex portfolios align with investor preferences, optimizing both return potential and risk exposure. Real-time AI monitoring continuously refines factor-based selections, adapting to market fluctuations. Traders benefit from automated portfolio adjustments, enhanced diversification, and systematic risk management. Financial institutions and hedge funds leverage AI-driven factor models to create efficient forex investment strategies. However, human oversight remains crucial to validate AI-generated insights and incorporate qualitative factors like central bank policies and economic shifts.