Risk assessment frameworks, such as those used for GM crops, have detailed comparative analysis with appropriate non-GM counterparts as their cornerstone. Opinions have been voiced that current analytical approaches are too specific and need to be complemented by more unbiased, larger scale analysis of gene expression and protein expression using transcriptomics and proteomics, respectively. In parallel, the use of metabolomics has been advocated as an approach to expand significantly the range of metabolites that can be measured to assess more stringently the potential for any unintended effects. Transcriptomics, proteomics and metabolomics have been termed collectively “omics” technologies. This review assesses the potential for using “omics” techniques in risk assessment. Importantly, the review provides information on sources of natural variation which can result from crop management practices, from interactions between genotype and growing environment and from non-GM breeding systems. This provides an important benchmark for risk assessors and risk managers.