In a rapidly evolving landscape of AI-driven customer support, adapting leadership and processes to effectively leverage AI metrics has become crucial. This shift is exemplified by the introduction of the CX Score, a tool designed to analyze conversations and provide a comprehensive view of support experiences. Unlike traditional metrics like CSAT, the CX Score handles a significantly larger data volume, necessitating new strategies for data analysis and interpretation, such as using it for trend reviews and targeted evaluations. A key challenge in this transition is accepting the "black box" nature of AI, where the focus shifts from understanding detailed processes to appreciating broader outcomes and insights. Embracing the emotional aspect of these changes is also essential, allowing teams to process feelings and celebrate achievements. As AI technology continues to advance, including improvements in explanations and summaries, the benefits of AI metrics are increasingly outweighing the drawbacks, encouraging experimentation and adaptation in customer service approaches.