Over the last decade, we have been facing a new aetiology responsible for the development of HCC - the non-alcoholic fatty liver disease (NAFLD). The prevalence of HCC development in this group is higher than that observed in the general population and in non-cirrhotic subjects with other causes of liver disease. Conventional ultrasound (US) is the first-line tool for HCC surveillance, but, in this population, it has a decreased diagnostic accuracy due to several particular features, including obesity and steatosis. Contrast-enhanced ultrasound (CEUS) appeared as a new branch of US due to its ability to depict the vascular architecture of all types of focal lesions (FLs). Nevertheless, CEUS has several limitations besides those inherited from US, which renders this method unreliable as the first-line HCC diagnostic tool and for HCC staging. Artificial intelligence eliminates operator limitations, which has led to an increased sensitivity and specificity of US. However, this approach is still in its early stages and more data are needed. Consequently, the purpose of the current study is to highlight the strengths and limits of US, along with its alternatives to HCC screening in NAFLD population.