Life Trajectories in AI Adoption among Elderly Consumers: Evidence and Implications through the Lens of the Life Course Paradigm

The pervasive diffusion of artificial intelligence (AI) in daily services makes it urgent to understand how older adults evaluate, adopt, or resist these technologies. This study adopts the Life Course Paradigm (LCP) to explain heterogeneity beyond traditional attitudinal models. A Theme-based Structured Systematic Literature Review of Englishlanguage studies indexed in Scopus (2016–03/2025) identified and coded 205 articles against LCP constructs reported in line with PRISMA 2020. Findings indicate that late-life engagement with AI is a trajectory rather than a one-off act: it is triggered by life events/transitions (T1), shaped by adaptation processes (socialization, stress–coping, and changes in human capital), and consolidated as outcomes (T2) within contextual variables—timing/duration (Ts), agency/prior experiences (Ps), and structural factors (Ss). Three managerial implications follow: (i) temporally calibrated interventions at salient transitions with scheduled follow-ups; (ii) cognitively calm, explainable interfaces supported by task-based micro-learning; and (iii) combining product-level agency (controls, reversibility) with ecosystem-level access (proximity services, accessibility standards). A research agenda is outlined on longitudinal dynamics (timing, duration, spacing), the agency–structure–emotion interplay, and place-based comparisons to inform policies and designs for inclusive AI in later life.