Abstract : Cancer incidence is steadily progressing worldwide, in parallel with the aging of the population. Workload is increasing constantly, especially in the fields of oncology and radiotherapy. This is particularly worrysome, as there is a general shortage of skilled professionals in the field (for example in medical physics). Moreover, every single patient does represent an enormous amount of data issued from a wide range of sources. This is especially true as far a medical imaging is concerned. Extraction of morphological data (anatomical location and extent of the tumour) and functional data (tumour biology and metabolism in general) becomes laborious. Moreover, images contain information which cannot be discerned by the human eye. Therefore, to handle shortage of human resources and transform this enormous amount of data automatically, artificial intelligence becomes a «must have». We intend to highlight the growing importance of radiomics as a cornerstone in automation of processes in radiotherapy, especially for treatment planification and a more personalized individualized treatment approach.