Evolution of artificial intelligence at Hospital Italiano de Buenos Aires: A retrospective review of experience and lessons learned.

BACKGROUND: Hospital Italiano de Buenos Aires (HIBA) has progressively integrated artificial intelligence (AI) technologies into clinical practice over more than two decades. Describing this process may provide useful insights for healthcare institutions aiming to adopt AI in a structured and sustainable manner. OBJECTIVES: To describe the evolution of AI implementation at HIBA, identifying key stages, technologies, and lessons learned throughout this institutional journey. METHODS: A retrospective institutional review was conducted, describing four sequential stages of AI adoption at HIBA. Each stage was characterized according to the predominant AI technologies, their clinical applications, and their degree of integration into routine healthcare workflows. RESULTS: The first stage (1997-2009) focused on establishing digital foundations and clinical decision support systems, improving patient safety through pharmacological alerts and structured clinical recommendations. The second stage (2010-2017) involved natural language processing and speech technologies, enabling the extraction of structured information from unstructured clinical text and the development of automatic speech recognition systems. The third stage (2018-2022) encompassed computer vision applications in medical imaging, including convolutional neural networks for breast density assessment and triage systems for chest radiographs, with emphasis on iterative validation and integration into clinical workflows. The fourth stage (2023-present) explores generative AI and large language models, exemplified by the internally developed chatbot TANA, supporting clinical decision-making, digital triage, and patient engagement. Across all stages, key lessons emerged related to data quality, interdisciplinary collaboration, model validation, user training, ethical safeguards, and responsible AI implementation. CONCLUSIONS: This overview highlights the institutional strategies and challenges associated with long-term AI adoption in healthcare. The experience at HIBA may offer relevant guidance for other hospitals seeking to integrate AI into clinical practice.