Does Generative Artificial Intelligence ( GAI ) Complement, Complicate, and Compromise Family Science Qualitative Analysis?

This article examines the relationship between generative artificial intelligence (GAI) tools and interpretive qualitative research in family science. Drawing on existing literature and an illustrative analytic comparison, we compare human‐led coding, ChatGPT‐assisted coding, and ATLAS.ti‐assisted coding (with GAI built in). In conversation with the literature and our analytic comparison, we consider how GAI tools complement, complicate, and compromise meaning‐making processes central to interpretive qualitative family research. Considering both the literature and our comparison, we conclude that GAI can complement analysis by supporting organization, comparison, and early pattern recognition, but it also complicates and compromises analysis by shifting analytic labor from deep human engagement toward more rote prompt design, output verification, codebook cleanup, and documentation, dampening human insights, creativity, and judgment.