A review on AI techniques for cost optimization and forecasting in SAAS infrastructure

Laxkar, Pradeep (2025) A review on AI techniques for cost optimization and forecasting in SAAS infrastructure. World Journal of Advanced Engineering Technology and Sciences, 16 (1). pp. 375-384. ISSN 2582-8266

The combination of Artificial Intelligence (AI) and Software as a Service (SaaS) platform has transformed the system of management of every available resource, allowing highly intelligent automation and increased scalability, as well as informed decision-making based on data. The current paper contains a detailed literature review of different machine learning (ML) techniques, including deep learning (DL), reinforcement learning (RL), etc., used to optimize resources deployed in SaaS environments. It discusses ways in which Artificial Intelligence (AI) can be used to increase cost-efficiency, boost service quality, enable predictive analytics and manage resources on the fly. What is also discussed in the study are the recent tendencies and strategies relying on AI to reinvent SaaS procedures and create user satisfaction. It also puts more focus on how AI can affect workload prediction, auto scaling of resources, and monitoring in real time, which are all part of operational excellence. It is with the help of this review that the paper seeks to give an insight into the changing importance of AI in SaaS applications and how its use can influence the future of cloud-based solutions. The results confirm the increasing significance of the AI-based solutions to the management of complicated SaaS infrastructures within an efficient environment. The next step in developing AI is further improvement of adaptability and responsiveness in the control of SaaS resources.