Personal AI assistants have changed how people use institutional and professional advice. We study this new strategic setting in which individuals may stochastically consult a personal AI whose recommendation is predictable to the focal advisor. Personal AI enters this strategic environment along two dimensions: how often it is consulted and how much weight it receives in the human's decision when consulted. Anticipating this, the advisor responds by counteracting the personal AI recommendation. Counteraction becomes more aggressive as personal AI is consulted more often. Yet advisor performance is non-monotone: equilibrium loss is highest at intermediate levels of adoption and vanishes when personal AI is never used or always used. Trust affects performance through a single relative influence index, and greater relative influence of personal AI increases advisor vulnerability. Extending the framework to costly credibility building, we characterize how personal AI adoption reshapes incentives to invest in trust.

翻译：个人AI助手已经改变了人们获取机构与专业建议的方式。本研究探讨了这一新型战略情境：个体可能随机咨询个人AI，而其推荐对核心顾问而言是可预测的。个人AI通过两个维度介入这一战略环境：被咨询的频率以及在人类决策时被赋予的权重。顾问通过抵消个人AI的推荐来预判并应对这一变化。随着个人AI被更频繁地咨询，抵消行为会变得更加强烈。然而顾问的绩效呈现非单调性：均衡损失在中等采用水平时最高，而在完全不使用或始终使用个人AI时趋于消失。信任通过单一相对影响指数作用于绩效，个人AI相对影响力的增大会加剧顾问的脆弱性。通过将框架扩展至成本可信度建设，我们刻画了个人AI采用如何重塑信任投资激励。