[Artificial intelligence and cardiovascular biobanks: Shared technological promise and ethical responsibility]

The implementation of artificial intelligence (AI) in biobanks and cardiovascular tissue banks constitutes a structural transformation with a significant impact on precision medicine, translational research, and the management of biomedical resources. These technologies enable the optimization, storage, and allocation of tissue classification, improve sample traceability, and allow the integrated analysis of large volumes of clinical, histological, and genomic data. However, their adoption introduces ethical, technical, and epistemological challenges that go beyond a purely instrumental perspective. The use of algorithms in clinical contexts poses risks such as excessive automation, the opacity of predictive models, the reproduction of biases, breaches of donor privacy, and the handling of sensitive genomic data. In addition, increasing reliance on automated systems may displace expert judgment and generate a false perception of objectivity. This article analyzes these implications and proposes a framework for the responsible implementation of AI in cardiovascular biobanks, based on principles of equity, transparency, data governance, clinical applicability, and respect for autonomy, emphasizing that their value depends on their ethical and scientific robustness. All of this is aimed at strengthening social trust, scientific quality, and sustainable clinical benefit.