Creating realistic and expressive character animations is a major challenge in video game development and interactive applications. Traditional methods, such as keyframing and motion capture, demand considerable time and resources. Recently, AI-driven text-to-motion models, especially diffusion models, have emerged as a promising alternative, allowing for the automatic creation of animations from textual descriptions. This thesis offers a comparative analysis of different motion generation models, focusing primarily on diffusion-based techniques. The evaluation examines crucial factors like motion quality, realism, adherence to prompts, and usability in real-time applications. To connect AI-generated animations with game engines, a specialized tool was developed to enable the seamless integration of these models into Unity, providing a practical workflow for developers.