Example Concept: AI models for financial forecasting rely heavily on historical data to predict future trends. In volatile markets, these models may not account for unforeseen events or shifts, leading to potential inaccuracies. Additionally, overfitting to past data can cause models to miss emerging patterns, while underfitting may result in overly simplistic predictions that don't capture market complexities.