This paper integrates artificial intelligence into affordance management to quantify and simulate perceived opportunities and threats across the life course. Using computer vision, reinforcement learning, and digital twins, we outline methods to capture objective social indicators, model adaptive strategies, and test counterfactual scenarios. These approaches advance evolutionary and developmental psychology from descriptive to predictive frameworks, enhancing the study of cognitive recalibration and enriching the empirical and theoretical understanding of human adaptation.