Harnessing the power of genomics is forcing a rethinking of aquaculture breeding. Successful breeding programs will always be built on the careful selection of the next generation of broodstock, detailed record keeping, and accurate, consistent collection of phenotypic data. Genomics allows this base of phenotype and selection to be enhanced, and ultimately accelerated to increase genetic gain per generation. From a breeding perspective, the need for biosecurity is balanced against bringing in genetics from growout ponds. In many cases, superior animals in growout ponds are not allowed to be brought into the breeding nucleus and incorporated into the breeding program due to risk of disease transfer. Similarly, selection for other traits such as disease resistance and carcass quality prevent broodstock on which a trait is measured from returning and contributing to the breeding nucleus. Thus, the only way to use this information for genetic improvement is to rely on family information. This approach is not ideal as the accuracy of selection is limited because within family genetic effects are not captured. Mass selection approaches suffer from the same shortcomings in biosecurity, lose potential increases in genetic gain to reduced accuracy, and suffer from the risk of inbreeding depression. Genomic selection was developed to increase the accuracy of selection, accelerate genetic gain, and consequently increase genetic gain per generation while simultaneously allowing for the control of inbreeding on a whole-genome level. It relies on the measurement of genomic similarity to predict breeding values, rather than a sib-ship relationship. It is a powerful tool for many reasons: 1) it allows for increases in selection accuracy; 2) it allows for selection of breeding candidates from different genetic backgrounds that are more likely to perform well; 3) it allows for the control of inbreeding (relatedness) in a genome wide fashion; 4) it allows for selection on phenotypes that cannot be measured on the breeding candidates without depending solely on family information. This last point can have a great impact on shrimp breeding, as it allows the accurate incorporation of genetic data from ponds without increasing biosecurity risks. Application of genomic selection is feasible with an economically efficient method for scanning the genome of broodstock and progeny for SNP (single nucleotide polymorphism) markers, using either sample volume or genomic imputation to reduce the overall burden of genotyping costs without sacrificing accuracy. With recent genotyping innovations in our laboratory, the economic costs for incorporating genomic selection to accelerate shrimp breeding programs are no longer barriers to implementation.