Understanding adaptive genetic variation is key for predicting the evolutionary response of species and populations to climate change, decisively influencing management and conservation decisions. Landscape genomics provides a framework to disentangle the effects of local adaptation from those of geographic distance and demographic history, through genomic analysis and the modeling of genotype-environment relationships. This approach can inform how evolutionary forces shape the neutral and adaptive genetic structure, helping to identify those populations subject to a greater risk of maladaptation due to anthropogenic climate change, i.e., the "genetic offset". Using restriction-site associated DNA sequencing (RAD-Seq) and more than 49,000 single nucleotide polymorphisms screened from 12 locations of Araucaria araucana in Chile, we assessed the genetic structure and predicted the genetic offset of this emblematic tree species under two future climate scenarios. Using generalized dissimilarity modeling (GDM) we found that the temperature annual range was the most important variable shaping the observed patterns of adaptive divergence. Our results show that populations living in the piedmont of the southern Andes Mountain range are at the greatest risk of maladaptation, while populations living in the high elevation zones in the Andes Mountain range are at the lowest risk. This study constitutes an important tool for forestry management and conservation of A. araucana forests.