Recent advancements in human-centric entertainment AI: challenges and benefits

Purpose This paper aims to review and analyze recent advancements in human-centric artificial intelligence (AI) systems designed for interactive entertainment environments. It emphasizes how AI technologies are reshaping human–machine interaction (HMI), enabling adaptive, personalized and immersive experiences for users across entertainment modalities. Design/methodology/approach The authors conduct a systematic review of AI applications across a wide range of entertainment types, including role-playing, simulation, strategy and sandbox environments. The study categorizes technical advances in procedural content generation, player modeling, reinforcement learning and natural language processing. Special attention is given to interaction paradigms such as user-agent collaboration, multimodal inputs, affective computing and co-creative interfaces. The methodology further analyzes how these components contribute to meaningful and dynamic HMI design. Findings AI technologies in entertainment are moving beyond rule-based systems toward context-aware, behavior-driven architectures. These systems enable emotionally responsive, adaptively personalized and cognitively rich interaction loops. However, challenges remain in explainability, transparency, data ethics and the transferability of user models across entertainment domains. Originality/value This paper bridges the gap between AI innovation and interactive entertainment design by reframing entertainment AI through the lens of HMI. It identifies key benefits such as increased engagement and creative empowerment, while also proposing a future-oriented roadmap to address technological and ethical challenges in deploying human-centered AI systems for entertainment.