JPEG image coding standard has been a dominant format in a wide range of applications in soon three decades since it has been released as an international standard. The landscape of applications and services based on pictures has evolved since the original JPEG image coding algorithm was designed. As a result of progress in the state of the art image coding, several alternative image coding approaches have been proposed to replace the legacy JPEG with mixed results. The majority among them have not been able to displace the unique position that the legacy JPEG currently occupies as the ubiquitous image coding format of choice. Those that have been successful, have been so in specific niche applications. In this paper, we analyze why all attempts to replace JPEG have been limited so far, and discuss additional features other than compression efficiency that need to be present in any modern image coding algorithm to increase its chances of success. Doing so, we compare rate distortion performance of state of the art conventional and learning based image coding, in addition to other desired features in advanced multimedia applications such as transcoding. We conclude the paper by highlighting the remaining challenges that need to be overcome in order to design a successful future generation image coding algorithm.