Research on Artificial Intelligence (AI) for Cloud Reliability focuses on leveraging AI techniques to enhance the dependability, fault tolerance, and performance predictability of cloud computing systems. This area addresses challenges such as dynamic workloads, resource failures, multi-tenant contention, and complex cloud infrastructures, where traditional reliability management approaches may be insufficient. Key research directions include predictive failure detection using machine learning and deep learning models, AI-driven fault-tolerant resource allocation and task scheduling, and anomaly detection for proactive maintenance. Other emerging topics involve reinforcement learning for adaptive reliability optimization, AI-based SLA compliance monitoring, and intelligent orchestration for cloud–edge–fog hybrid systems. Additionally, research on self-healing cloud infrastructures, AI-assisted replication and migration strategies, and predictive reliability analytics represents significant avenues for advancing resilient, autonomous, and efficient cloud computing environments.