The current state of AI in enterprises is marked by frustration due to its unreliability and inability to deliver on its promises, particularly in high-stakes industries like healthcare and banking. The prevalent methods of deploying AI—either relying on unpredictable large language models or using rigid, hard-coded solutions—are inadequate. These approaches fail to provide the necessary reliability and scalability, leaving enterprises in a cycle of re-engineering and uncertainty. The text proposes a new paradigm called Guaranteed AI Performance, centered around Quality Level Agreements (QLAs) that promise predictability, transparency, and cost control in AI systems. This approach could revolutionize AI by enabling it to plan and execute tasks with precision, thus transforming AI from a gamble into a trusted, integral part of enterprise infrastructure.