In this review, we discuss the management of genomic medicine, which is based on very large data sets with up to billions of data points when analysing the whole genome. By using artificial intelligence (AI) it is possible to find patterns in such data sets and thereby identify subgroups of patients differing clinically, or to extract informative data points and construct models, which will predict disease risk, prognosis or treatment response most often in a process including training and testing (machine learning). Future clinical decision making will increasingly be based on patterns and models obtained by AI analysis of many parameters.