From Screening to Retention: Extending AI Bot Roles Across the Employee Lifecycle: A Case Study of a Mobile Game Studio

Abstract

AI bots in HR are generally associated with recruitment and are rarely carried over to other stages of the ELC. Moreover, while traditional bigtech companies are often the subject of the research, the gamedev industry - with its project-based structure, heterogeneous teams, and crunch culture - remains an under-researched case in the context of AI and HR. On the basis of this context, our research question was: How does AI adoption vary across the stages of the employee lifecycle? Focusing empirically on recruitment as a best-case scenario, to what extent does this pattern hold across heterogeneous roles within a game development studio? As a method, the insider single case-study on the example of an anonymised small game studio was chosen. We conducted the comparison of HR metrics before and after implementation of AI tools on the team level and, separately, creative roles. The key finding was that process metrics reduced by 60–77% in both segments; at the same time, those in creative roles achieved comparable or better results than the team as a whole, contrary to the expectations of the heterogeneity hypothesis. Our contribution consists of the development of a theoretical framework (Differential AI Adoption), a refinement showing that tool design (custom-built vs. generic) may matter more than role type; and a practical recommendation for small studios.