This paper introduces the Asymmetric Integration Model (AIM), arguing that in post-LLM digital environments, automation generates conversational scale while humans supply consequence-bearing legitimacy. As optimisation regimes prioritise engagement density and persistence, affective cost is distributed to participants while control remains centralised. The proposed framework shifts debate from content moderation to architectural design, outlining pathways to rebalance asymmetry without rejecting human–machine integration.