The customer service landscape is experiencing a monumental shift as AI becomes more advanced, enabling support teams to focus on activities that create additional value for their customers. Traditional metrics such as first response time (FRT), average handle time (AHT), and cases handled are evolving to reflect the changing nature of customer interactions. New metrics like automated resolution rate, first contact resolution (FCR), time to resolution (TTR), content views, net promoter score (NPS), customer effort score (CES), internal quality score (IQS), return on investment (ROI), bot involvement rate, bot engagement rate, and conversational insights are emerging as a result of AI. Support leaders must adapt their reporting approach to measure the right things in this unfolding era of customer service, focusing on both customer and teammate experiences. By leveraging data from AI-powered chatbots, support teams can gain valuable insights to improve their systems and processes, enhance their reporting capabilities, and unlock easier ways to measure quality and performance.