Seeing Less, Engaging More: Rethinking Early User Experience on Generative AI Cocreation Platforms—Findings from a Field Experiment

Generative artificial intelligence (GenAI) content generation (GCG) platforms enable users to cocreate personalized content with remarkable speed. Yet recent research suggests that such immediacy may undermine early engagement. When content appears instantly, users may not realize sufficient value to register on the platform. We address this challenge by introducing fulfillment, that is, the extent to which cocreated content is revealed prior to registration on GCG platforms, as an experiential design lever that shapes value realization in initial interactions. Drawing on value cocreation literature, we suggest that fulfillment operates through two motivational pathways: value-in-use, reflecting users’ recognition that their input meaningfully shaped the output, and curiosity, reflecting anticipatory motivation when the experience remains perceptually open. Using a randomized field experiment on a GCG platform, complemented by a follow-up online experiment, we show that partial fulfillment, which reveals some but not all generated output, outperforms both full and no fulfillment in driving registration. This effect is also conditioned by the framing of the registration message. Although loss-framed messages that emphasize the cost of inaction increase registration on average, this effect attenuates under full fulfillment, suggesting a substitution relationship. Formal mediation analyses indicate that although both full and partial fulfillment enhance value-in-use, only partial fulfillment sustains curiosity, and this dual activation explains its effectiveness. Additional analyses delineate the scope of these effects, which persist beyond registration to shape subsequent engagement and return behavior, but arise only when users meaningfully coproduce content and are enhanced by better quality outputs. Together, these findings suggest that registration on GCG platforms depends not on maximizing disclosure or curiosity alone, but on structuring interactions to preserve users’ involvement in shaping generated outputs. In doing so, they highlight how effective design on GCG platforms supports engagement that emerges from complementary human and GenAI contributions, rather than from automation alone.

History: Indranil Bardhan, Senior Editor; Gordon Burtch, associate editor.

Funding: The authors acknowledge financial support from the National Natural Science Foundation of China [Grants 72522025 and 72402163].

Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2024.1200.