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Abstract Aortic stenosis, a major contributor to global cardiovascular morbidity, is expected to increase in prevalence as populations age, potentially doubling by 2050. The past decade has witnessed a seminal shift in the diagnosis and management of aortic stenosis, driven largely by innovations in transcatheter therapies and advances in diagnostic precision. Modern echocardiographic techniques, including three dimensional imaging, cardiac computed tomography, and AI driven imaging have transformed patient care, enabling earlier disease detection, more accurate risk assessment, and individualized treatment planning. The advent of transcatheter aortic valve replacement (TAVR), validated across all surgical risk categories, has redefined therapeutic paradigms, emphasizing patient centered decision making by using multidisciplinary heart teams. Despite these breakthroughs, challenges remain, particularly regarding optimal management strategies for bicuspid valve disease, asymptomatic severe aortic stenosis, moderate aortic stenosis, and younger patient populations, who present unique considerations related to long term valve durability and lifetime intervention sequencing. Furthermore, challenges surrounding valve thrombosis, stroke risk, and structural valve degeneration persist. Artificial intelligence might be able to address some of these challenges, potentially refining risk stratification, procedural execution, and long term follow-up. This review critically appraises contemporary diagnostic and therapeutic developments in aortic stenosis, explores emerging evidence, summarizes nuances in American and European guidelines, and identifies pivotal knowledge gaps that require future research to optimize patient outcomes.