AI-powered forex risk-adjusted return optimization enhances trading strategies by balancing profitability with risk management. Using machine learning algorithms, AI analyzes vast amounts of historical price data, volatility patterns, macroeconomic indicators, and interest rate differentials to optimize returns while minimizing risks. AI-driven predictive models identify favorable trading opportunities based on expected returns and risk exposure. One of the key techniques AI employs is Sharpe ratio optimization, which adjusts forex portfolios to maximize returns relative to risk. AI also applies Value-at-Risk (VaR) models to assess potential losses under different market conditions. Additionally, reinforcement learning algorithms adapt to market fluctuations, continuously refining trading strategies for improved performance. AI-powered real-time risk monitoring ensures traders can react instantly to market changes, reducing drawdowns and protecting capital. By integrating stop-loss mechanisms, automated hedging strategies, and currency diversification techniques, AI helps traders achieve consistent, risk-adjusted gains. Financial institutions and hedge funds use AI-driven risk-adjusted optimization tools to develop efficient forex portfolios. However, human oversight remains essential to validate AI recommendations and consider external factors like geopolitical events and central bank policies.