This perspective paper argues that Explainable AI (XAI) combined with causal reasoning is essential for extracting scientific insights from complex AI models that often outperform human capabilities. It proposes XAI as a unifying framework to foster human-AI collaboration across scientific discovery, engineering optimization, and system certification.