Cardiovascular risk assessment is a natural extension of lung cancer screening (LCS) because individuals eligible for low-dose computed tomography often carry a high burden of cardiovascular risk, and cardiovascular disease remains a major competing cause of morbidity and mortality. The same examination can provide clinically relevant cardiovascular information, particularly through coronary artery calcium (CAC) assessment, without additional imaging, radiation exposure, or patient burden. Visual, semi-quantitative, and automated approaches support the prognostic value of CAC detected on non-gated chest computed tomography. No prospective outcome trial has yet shown that intervention on CAC detected during LCS reduces events. However, a long-term follow-up analysis of a randomized LCS trial found that CAC reporting was associated with lower cardiovascular mortality, likely reflecting improved risk recognition and greater use of preventive care. Implementation of simultaneous LCS and CAC screening should therefore be pragmatic, with standardized reporting, clear preventive care pathways, and prospective evaluation of treatment initiation, adherence, outcomes, cost-effectiveness, and potential unintended consequences. Artificial intelligence may help standardize CAC assessment, extract cardiovascular phenotypes beyond conventional scoring, and support integrated thoracic and cardiovascular prevention.