This paper presents the results of a study on human partner selection strategies and AI-induced competitive pressures in a situation where large-scale language model (LLM)-based artificial agents compete with humans as cooperative partners. We conducted three experiments (N=975) using a communication-based partner selection game that simulated a mixed society consisting of humans and LLM-based bots. The results show that bots are more prosocial and linguistically distinguishable than humans, but are not preferentially selected when their identities are hidden. Humans tend to misinterpret the bots’ behavior as human behavior, and vice versa. When the bots’ identities were revealed, the bots’ initial selection probability decreased, but they gained a competitive advantage over humans over time by allowing humans to learn about the behaviors of each partner type. In conclusion, AI can reorganize social interactions in mixed societies and provide Takeaways for the design of more effective and cooperative mixed systems.