Artificial Intelligence and Echocardiography: From Literacy to Leadership, Redefining Roles, Responsibilities, and...

Artificial intelligence (AI) is rapidly reshaping echocardiography, evolving from experimental applications to regulated clinical tools that automate acquisition, quantification, and outcome prediction. Yet for many practitioners, AI terminology remains elusive and disconnected from routine care. This review provides an educational and conceptual framework to bridge technical innovation with clinical reasoning. We outline the foundations of AI literacy, covering machine learning, deep learning, dataset construction, and validation, while appraising the literature through contemporary methodological standards for cardiovascular imaging AI. We then describe four progressive levels of clinical value, from automation and standardization to disease phenotyping, prognostic modeling, and sustainability. Particular emphasis is placed on explainable AI, governance models, AI-ready laboratories, and the need for external validation and postdeployment accountability. Beyond efficiency, AI has ethical and societal implications: Cloud-based platforms and hub-and-spoke models may democratize access to high-quality echocardiography, supporting more equitable global care. Finally, we discuss evolving professional roles, educational frameworks, and the integration of generative and multimodal AI. The overarching goal is to guide clinicians from basic literacy to informed leadership in an era where echocardiography is increasingly AI-integrated rather than merely AI assisted.