Enterprises face challenges in selecting optimal large language models (LLMs) for applications, emphasizing empirical evaluation over hype. Key steps include defining task-specific KPIs, benchmarking models on platforms like Amazon Bedrock, and balancing cost, scale, and specialization. Ongoing monitoring ensures ethical performance, turning AI into a sustainable competitive advantage.