There is an urgent need in forest tree species to accelerate the breeding cycle and to change the seed orchard production profiles from solely one of improved growth, to that of improved climate resiliency. Genomic prediction and genome-wide association analyses are currently being seen as powerful tools to facilitate the rapid selection of superior genotypes and to identify alleles or genomic regions of complex traits in forest tree species. In this presentation, I will focus on different quantitative genetic and genomic tools and how to fully integrate genomic data linked to productivity- and climate change-related (adaptive) traits in two conifer tree-breeding programs: Pinus contorta Dougl. (interior lodgepole pine) and Picea glauca (Moench) Voss (white spruce), managed by the forest industry and Government of Alberta (Canada), respectively. The results of these studies, presented in three recent scientific publications, illustrate the advantages of using genomic information jointly with productivity and climate-adaptability traits, to enhance the identification and selection of genetic material of these two boreal conifer tree species for the production of resilient and sustainable forests in a changing climate context.