Example Concept: Integrating AI models often requires adapting existing software architecture to accommodate new data processing pipelines, ensuring the AI model's outputs are compatible with current system interfaces, and managing computational resources to prevent performance bottlenecks. Additionally, developers must consider data privacy and security, as well as the need for continuous model updates and monitoring to maintain accuracy and relevance.