AI applications can look affordable during development but become expensive once real users start using them. A chatbot may receive thousands of requests, an image-generation tool may need substantial computing power, and an AI-powered business application may require resources throughout the day. The challenge is not simply finding a Cheaper Server. It is understanding where computing resources are being used and choosing infrastructure that matches the workload. AI inference cost optimization helps businesses manage the cost of running trained AI models while maintaining the response times and reliability their users expect.