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This paper presents an empirical study of AI coding agent contributions in open-source Android and iOS mobile app development by analyzing 2,901 AI-authored pull requests (PRs) from 193 GitHub repositories. The study reveals that Android projects receive more AI-authored PRs and exhibit higher acceptance rates compared to iOS, with routine tasks showing higher acceptance rates than structural changes. The analysis also indicates an initial improvement followed by a decline in PR resolution time on Android, providing insights into the evolving impact of AI agents on OSS mobile projects.
Android projects are twice as likely to accept AI-authored code contributions compared to iOS, revealing platform-specific biases in the adoption of AI coding agents.
AI coding agents are increasingly contributing to software development, yet their impact on mobile development has received little empirical attention. In this paper, we present the first category-level empirical study of agent-generated code in open-source mobile app projects. We analyzed PR acceptance behaviors across mobile platforms, agents, and task categories using 2,901 AI-authored pull requests (PRs) in 193 verified Android and iOS open-source GitHub repositories in the AIDev dataset. We find that Android projects have received 2x more AI-authored PRs and have achieved higher PR acceptance rate (71%) than iOS (63%), with significant agent-level variation on Android. Across task categories, PRs with routine tasks (feature, fix, and ui) achieve the highest acceptance, while structural changes like refactor and build achieve lower success and longer resolution times. Furthermore, our evolution analysis shows improvement in PR resolution time on Android through mid-2025 before it declined again. Our findings offer the first evidence-based characterization of AI agents effects on OSS mobile projects and establish empirical baselines for evaluating agent-generated contributions to design platform aware agentic systems.