The move towards a cloud-based digital transformation has taken enterprise reliability from being merely a concern of the back office to making it a strategic capability. In Saudi Arabia this transition is supported by Vision 2030, the quick adoption of cloud technology, national investment in artificial intelligence, and the increasing reliance by both public and private organisations on digital services that are always available. Although traditional IT service management is still useful for controlling processes, its reliance on manual triage, monitoring based on thresholds, fragmented telemetry, and human-led diagnosis is becoming more and more strained as a result of distributed cloud architectures. This study brings together research that was published between 2020 and 2025 on the use of artificial intelligence in IT operations, cloud failure prediction, log and trace analytics, incident intelligence, root-cause analysis, automated remediation, and intelligent service desks. The objective is to see how these capabilities can be combined into a governable operating model for businesses in Saudi Arabia rather than being implemented as separate algorithms. The evidence shows that AI can enhance early detection of failures, the classification of incidents, prioritisation, causal diagnosis, knowledge retrieval, and certain remediation tasks, but its performance is very much dependent on the quality of the telemetry, the service topology, controls against model drift, explainability, and the limits set on autonomous action. The paper puts forward a framework for AI-enabled Cloud Operations and Intelligent IT Service Management based on five layers: observability, context, intelligence, orchestration, and governance. It also defines a closed-loop assurance lifecycle in which machine-generated recommendations are continuously assessed in relation to service-level, risk, security, and business outcomes. The review concludes that the most significant contribution of Vision 2030 will be achieved through the controlled enhancement of human operations, not through uncontrolled automation, and it identifies key areas such as Arabic-aware service intelligence, cross-enterprise benchmarking, sovereign data controls, and measurable human-AI accountability.