Content area
This thesis explores the impact of integrating Generative AI on game development architectures in Unity, focusing on comparing Unity’s traditional GameObject system to its more recent Entity-Component-System (ECS). As generative AI, particularly in textual content, becomes more prevalent in content generation, understanding how different architectural paradigms handle the integration of AI-driven content is crucial for optimizing both performance and creative workflows. The GameObject system, known for its ease of use and modularity, has been the backbone of Unity for many years, while ECS offers a data-oriented approach designed to maximize performance and scalability. This research investigates the strengths and limitations of both systems when integrating AI-generated content, analyzing factors such as performance, scalability, and ease of integration.
Through a combination of case studies, prototype development, and performance benchmarking, this thesis provides a comparative analysis of how generative AI content influences game design and architecture in Unity. The findings aim to inform developers about best practices for incorporating AI-generated narratives and highlight which architectural approach – GameObject or ECS – offers greater efficiency and flexibility in different game development contexts. Ultimately, this work contributes to the growing knowledge of the intersection of AI and game development, offering practical insights for future projects.