The convergence of AI and human induced pluripotent stem cell (hiPSC) platforms is redefining in vitro biological models. Advances in hiPSC-derived three-dimensional cardiac organoids, engineered heart tissues, and heart-on-chip systems have improved physiological relevance but generate high-dimensional, multimodal datasets that exceed the capacity of traditional analytical approaches. I will discuss how emerging computational approaches, including machine learning, deep learning, and generative AI, can unlock the full potential of engineered cardiac models.