Example Concept: When integrating AI models, developers often face trade-offs between model complexity and system performance. Complex models may offer higher accuracy but can increase latency and require more computational resources, impacting system responsiveness. Conversely, simpler models may run faster and use fewer resources but might not achieve the desired accuracy. Additionally, integrating AI can introduce maintenance challenges, requiring updates to both the AI models and the surrounding infrastructure to ensure compatibility and security.