Abstract Climate change (CC) necessitates reforestation/afforestation programs to mitigate its impacts and maximize carbon sequestration. But comprehending how tree growth, a proxy for fitness and resilience, responds to CC is critical to maximize these programs' effectiveness. Variability in tree response to CC across populations can notably be influenced by the standing genetic variation encompassing both neutral and adaptive genetic diversity. Here, a framework is proposed to assess tree growth potential at the population scale while accounting for standing genetic variation. We applied this framework to black spruce (BS, Picea mariana [Mill] B.S.P.), with the objectives to (1) determine the key climate variables having impacted BS growth response from 1974 to 2019, (2) examine the relative roles of local adaptation and the phylogeographic structure in this response, and (3) project BS growth under two Shared Socioeconomic Pathways while taking standing genetic variation into account. We modeled growth using a machine learning algorithm trained with dendroecological and genetic data obtained from over 2600 trees (62 populations divided in three genetic clusters) in four 48-year-old common gardens, and simulated growth until year 2100 at the common garden locations. Our study revealed that high summer and autumn temperatures negatively impacted BS growth. As a consequence of warming, this species is projected to experience a decline in growth by the end of the century, suggesting maladaptation to anticipated CC and a potential threat to its carbon sequestration capacity. This being said, we observed a clear difference in response to CC within and among genetic clusters, with the western cluster being more impacted than the central and eastern clusters. Our results show that intraspecific genetic variation, notably associated with the phylogeographic structure, must be considered when estimating the response of widespread species to CC.