AIOps, or Artificial Intelligence Operations, is emerging as a transformative force in IT operations by leveraging AI algorithms and data analytics to automate tasks and suggest solutions for common IT issues, thereby easing the workload on IT teams. Despite the promise of AIOps, its adoption faces challenges due to the complexity of modern cloud-native environments and the limitations of traditional machine learning approaches, which struggle with scaling and require significant human intervention. Deterministic AI, with its systematic fault-tree analysis, offers an alternative by providing immediate and precise root-cause analysis in real time, helping IT teams respond swiftly to anomalies and streamline operations. By enhancing alert management, automating processes, and reducing IT spend, AIOps solutions can drive efficiency and support digital transformation, yet their implementation is hindered by a lack of internal skills, a common data model, and effective frameworks for automation. As organizations seek to harness AIOps, platforms like Dynatrace are adopting deterministic AI to deliver comprehensive observability and automated insights, thereby enabling IT teams to focus on strategic priorities and innovation.