The diffusion of Generative AI (GenAI) constitutes a supply shock of a fundamentally different nature: while marginal production costs approach zero, content generation creates congestion externalities through information pollution. We develop a three-layer general equilibrium framework to study how this non-convex technology reshapes market structure, transition dynamics, and social welfare. In a static vertical differentiation model, we show that the GenAI cost shock induces a kinked production frontier that bifurcates the market into exit, AI, and human segments, generating a ``middle-class hollow'' in the quality distribution. To analyze adjustment paths, we embed this structure in a mean-field evolutionary system and a calibrated agent-based model with bounded rationality. The transition to the AI-integrated equilibrium is non-monotonic: rather than smooth diffusion, the economy experiences a temporary ecological collapse driven by search frictions and delayed skill adaptation, followed by selective recovery. Survival depends on asymmetric skill reconfiguration, whereby humans retreat from technical execution toward semantic creativity. Finally, we show that the welfare impact of AI adoption is highly sensitive to pollution intensity: low congestion yields monotonic welfare gains, whereas high pollution produces an inverted-U relationship in which further AI expansion reduces total welfare. These results imply that laissez-faire adoption can be inefficient and that optimal governance must shift from input regulation toward output-side congestion management.

翻译：生成式人工智能（GenAI）的扩散构成了一种本质不同的供给冲击：虽然边际生产成本趋近于零，但内容生成会通过信息污染产生拥塞外部性。我们构建了一个三层一般均衡框架，以研究这种非凸技术如何重塑市场结构、转型动态与社会福利。在一个静态纵向差异化模型中，我们证明GenAI成本冲击导致生产前沿出现拐折，将市场分化为退出、AI与人力三大区段，在质量分布中形成“中产空心化”。为分析调整路径，我们将此结构嵌入均值场演化系统及一个具有有限理性的校准多主体模型。向AI融合均衡的转型是非单调的：经济并非经历平滑扩散，而是因搜索摩擦与技能适应延迟而出现暂时的生态崩溃，随后进入选择性复苏阶段。生存取决于非对称的技能重构，即人类从技术执行向语义创造力领域收缩。最后，我们证明AI采纳的福利影响对污染强度高度敏感：低拥塞水平下福利呈单调增长，而高污染则产生倒U型关系，即进一步的AI扩张会降低总福利。这些结果表明自由放任的AI采纳可能缺乏效率，最优治理必须从投入侧监管转向产出侧的拥塞管理。