There are many exciting AI innovations in ultrasound imaging. Ultrasound, though, may face certain challenges when it comes to the implementation of these AI solutions. This is related, among other things, to the variability in data acquisition and diversity of equipment, as well as the dynamic nature of the images. The same limitations also open up a new field for exploring different opportunities in image acquisition support, ranging from recognition of optimal views to fully automated robotic scanning. More traditional AI areas of research have also been discussed in this chapter, such as image enhancement, segmentation and lesion classification using radiomic features. There are, however, still issues with the generalisability of results from the laboratory setting to diverse clinical practices. In particular, two specialist areas show great advancement in the application of AI across the entire imaging chain of sonography: cardiac echocardiography and obstetric ultrasound. These will be discussed in greater detail. In conclusion, AI holds promise to make ultrasound acquisitions faster and more reproducible, potentially alleviating the shortage of skilled radiographers.