Can AI identify shifts in market regimes earlier than traditional models?

Some traders argue that AI’s value in identifying market regimes lies not in predicting the next price move, but in detecting sooner when the market relationships a model relies on are beginning to break down—for example, when variables such as liquidity, volatility, and correlation change at the same time. Traditional quantitative models typically require measurable confirmation, such as volatility crossing a threshold or correlation moving outside its historical range. By then, part of the shift may already have occurred. But market noise can produce false alarms. The real challenge is to detect shifts earlier without triggering too many false alarms, and AI may be better suited as an early warning layer on top of traditional models.