AI-based risk-adjusted performance benchmarking is revolutionizing forex trading by providing objective and data-driven assessments of trading strategies. Using machine learning algorithms, AI evaluates historical returns, volatility, drawdowns, and Sharpe ratios to measure a trader’s performance against market benchmarks. AI-driven models analyze currency correlations, liquidity conditions, and macroeconomic factors to assess how effectively a forex portfolio balances risk and return. One key advantage of AI is its ability to generate customized benchmarks based on a trader’s risk appetite and strategy. AI applies Value-at-Risk (VaR) analysis, Monte Carlo simulations, and beta-adjusted performance metrics to compare trading outcomes with industry standards. Real-time AI monitoring enables continuous performance tracking, ensuring traders can adjust their strategies dynamically. AI-powered dashboards visualize profitability, risk exposure, and efficiency ratios, providing actionable insights for traders and institutional investors. Hedge funds and financial institutions use AI-driven performance benchmarking to refine algorithmic trading models and enhance portfolio management strategies. However, human oversight remains essential to interpret AI-generated insights and integrate qualitative factors like geopolitical risks and central bank policies.