Modeling the nonlinear impact of artificial intelligence on mobile game adoption and retention: a system dynamics approach for strategic decision support

Abstract Purpose The mobile gaming industry continues to face a persistent challenge of high churn rates that undermine long-term player retention and profitability. This study develops a hybrid system dynamics (SD) model that integrates the Bass diffusion framework to examine the systemic impact of artificial intelligence (AI) on adoption and retention dynamics in free-to-play mobile games. AI is endogenized as a dynamic stock that influences multiple reinforcing and balancing feedback loops related to personalization, content quality, word-of-mouth, and churn mitigation. The model is implemented in Vensim ® and validated against industry benchmarks. Scenario analyses of five key AI policy levers demonstrate that moderate AI investments strengthen reinforcing loops, leading to sustained player bases and higher cumulative revenue, whereas aggressive scaling activates balancing loops and results in volatility and reduced long-term performance. The simulation reveals clear trade-offs between short-term growth and long-term stability. By offering a simulation-based decision-support tool, this research provides managers with actionable insights for optimizing AI investment timing, marketing allocation, and feature deployment under resource constraints. The proposed SD–Bass hybrid advances management modeling methodologies and offers valuable implications for technology investment decisions in digital business environments.