Abstract

As generative artificial intelligence (GenAI) becomes increasingly embedded in digital products, understanding how users experience GenAI-enabled products has become an important research issue. Prior research on GenAI products has mainly examined relatively static AI-generated outputs, with particular attention to disclosure, algorithmic source, authenticity, and perceived value. However, this literature offers limited insight into digital games, where GenAI may be incorporated not only into pre-generated components such as assets, text, and audio, but also into runtime systems such as adaptive dialogue, characters, and gameplay content. To address this gap, this study develops a Needs-(Dis)Affordances-Features framework for understanding how GenAI-enabled technical features shape players’ psychological need satisfaction and frustration in digital games. Drawing on the needs-affordances-features perspective, disaffordance, and self-determination theory, we conduct a grounded theory analysis of 3,096 reviews from 810 digital games on Steam identified through platform statements indicating GenAI involvement. The findings suggest that player responses are shaped less by AI-related labels or source cues than by the specific technical features through which GenAI is incorporated into the game. GenAI-enabled features such as generated assets, dialogue, and adaptive systems give rise to affordances and disaffordances that support or frustrate autonomy, competence, and relatedness. This study extends research on GenAI products to digital games by showing how feature-level GenAI integration, rather than AI origin alone, shapes player experience.

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