Application Management Services (AMS) organizations have traditionally optimized for operational efficiency using metrics such as ticket volume, mean time to resolve (MTTR), and service-level agreement (SLA) compliance. While necessary, these measures are weak proxies for business outcomes and can inadvertently drive local optimization (e.g., faster closure over durable resolution). This article proposes a practical KPI architecture that connects AMS performance to product and enterprise value via a clear “line of sight” from operational signals to service health, customer experience, risk posture, and financial impact. We also describe how AI—spanning AIOps, automation, and generative AI—can accelerate this transformation by improving detection, triage, knowledge reuse, change risk management, and self-healing capabilities. Finally, we provide an implementation roadmap and governance model to operationalize business-focused KPIs while sustaining reliability, compliance, and continuous improvement.