Strategic Advice in the Age of Personal AI
This addresses the problem of strategic interactions in advice-giving for individuals and institutions in the age of AI, offering incremental insights into adoption dynamics.
The paper studies how personal AI assistants affect strategic advice-giving, finding that advisors counteract AI recommendations more aggressively as AI consultation frequency increases, leading to highest equilibrium loss at intermediate adoption levels and vanishing loss when AI is never or always used.
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.