Artificial Intelligence in Cloud Computing: A Systematic Literature Review of Applications, Challenges, and Future Directions

Abstract

The integration of Artificial Intelligence (AI) with cloud computing has emerged as an important research area for developing scalable, intelligent, and automated computing environments. Cloud computing provides on-demand access to computing resources, storage, networking, and software services, while AI and Machine Learning (ML) enable systems to analyse large volumes of data, make predictions, optimize resources, and automate decision-making. This review examines major applications of AI-enabled cloud environments, including intelligent resource management, load balancing, security monitoring, fault prediction, energy optimization, storage management, cost optimization, quality-of-service prediction, and edge-cloud intelligence. It also examines challenges including data privacy, security, computational cost, model explainability, interoperability, data dependency, and resource requirements. Future research directions include autonomous cloud management, federated learning, Explainable AI, AI-driven serverless computing, edge-cloud intelligence, foundation models, green AI, and AI-assisted cybersecurity. The review concludes that the convergence of AI and cloud computing provides significant opportunities for intelligent, scalable, secure, and sustainable computing systems.