Understanding adsorption competition mechanisms of molecules at solid interfaces is critical for industrial applications such as nanocomposite processing, synthesis and surface functionalization. The adsorption behavior of any molecule to a surface varies depending on the molecule-surface interactions, solvent environment and other competitive molecules in the environment. This competition between molecules is driven both by enthalpic and entropic effects. Even in the case of similar enthalpic molecule-surface interactions like those of polydisperse polymer melts competition of low and high molecular weight chains is highly present due to strong entropic effects. These competitive mechanisms are not fully understood. Here, we address this challenge through a multiscale simulation framework that integrates data driven machine learning models, which includes two main steps. First, we develop atomistic forcé fields (FFs) trained on density functional theory (DFT) data, [1,2] sampled during an active learning (AL) process.[2] Subsequently, the accurate FFs are utilized in large-scale atomistic molecular dynamics (MD) simulations.[3] We focus on three representative systems of increasing complexity: (i) polybutadiene chains of different lengths adsorbing on alumina surfaces, serving as a reference θ-solvent case dominated by entropic effects; (ii) poly(vinylpyrrolidone) (PVP) adsorption on silver surfaces in aqueous environments; and (iii) ligand-induced displacement of adsorbed PVP by small molecules, such as diethylamine, under varying hydration levels relevant to experimental and technological conditions.[4] We examine how solvent content, molecular size, and molecule–surface interactions control adsorption, desorption, and exchange at the molecular level. We focus on identifying the “rules” of adsorption competition and the dominant physical mechanisms and timescales that determine which molecules prevail. These insights aid the interpretation of experiments and guide the design of polymer-surface systems for industrial applications.