Does generative AI make us think alike? A systematic review and meta-analysis of homogenization effects in human–AI co-creation

Does generative AI make us think alike? As human–AI co-creation becomes embedded in creative practice, concerns have emerged that creative outputs may exhibit homogenization, as reduced diversity of meanings, across users, even when individual creativity improves. We address this concern through a systematic review and three-level meta-analysis of empirical studies on homogenization in human–AI co-creation (19 studies, 61 effect sizes). Results reveal a small but statistically significant homogenization effect associated with AI use, robust across sensitivity analyses and not explained by publication bias. Moderator analyses indicate that homogenization is task-sensitive, with stronger effects in semantically constrained ideation tasks than in minimally constrained divergent thinking tasks. Additional analyses suggest that homogenization may persist beyond co-creative episodes and extend to real-world contexts. Rather than indicating a loss of creativity, these findings point to a gradual, scale-dependent reorganization of creative diversity shaped by task structure, interaction workflows, and sociotechnical feedback processes.