Firms increasingly employ artificial intelligence (AI) gift recommendation tools to assist consumers with their gift choices. Yet, a notable gap exists in understanding consumers’ responses to AI recommendations in a gift giving context. Through five studies, we found that social closeness between the giver and recipient significantly ...
Firms increasingly employ artificial intelligence (AI) gift recommendation tools to assist consumers with their gift choices. Yet, a notable gap exists in understanding consumers’ responses to AI recommendations in a gift giving context. Through five studies, we found that social closeness between the giver and recipient significantly affects the use of AI gift recommendation tools, driven by two underlying mechanisms: expected relational signaling and preference matching. In addition to establishing these effects, this research identifies relevant boundary conditions. Our findings reveal that self-oriented perfectionism increases preference matching for gifts to distant friends, while revealing the giver's identity boosts AI tool use for close friends by reducing relational signaling expectations. Additionally, AI tools capable of turn-taking enhance preference matching and AI tool use, especially for gifts to close friends. Our findings advance the understanding of how and why social closeness influences givers’ utilization of AI gift recommendation tools and offer valuable insights for practitioners on designing these tools more effectively, considering the nuances of social relationships.
