Artificial intelligence (AI) is rapidly transforming bioengineering, with applications ranging from diagnosis and biomedical imaging to wearable technologies, rehabilitation, biomaterials, biofabrication, and digital twins. This narrative review aims to examine the major innovations, challenges, and future directions of AI-enabled bioengineering, with particular attention to its clinical and translational development. The literature was searched in Scopus and PubMed, with emphasis on systematic reviews and meta-analyses and consideration of other relevant secondary literature across the main bioengineering domains. A total of 57 secondary publications were included in the principal evidence base. The review process was additionally informed by the ANDJ Narrative Review Checklist and an established qualification and scoring methodology applied to the selected secondary literature. The reviewed evidence shows a broad expansion of AI applications and increasing integration of intelligent technologies into bioengineering systems. However, important challenges remain, particularly regarding data quality and representativeness, validation and generalizability, reproducibility, safety, human oversight, ethical responsibility, equity, and regulatory requirements. Future developments are expected to increasingly involve multimodal, adaptive, connected, and human-centered systems integrating AI with sensing technologies, robotics, digital twins, and longitudinal data. Overall, AI-enabled bioengineering is progressing from promising technological applications toward increasingly integrated and translational systems. Its successful evolution will depend on combining technological innovation with robust clinical evidence, responsible development, and appropriate ethical and regulatory frameworks.
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Daniele Giansanti (2026) studied this question.
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