The rapid adoption of cloud computing has revolutionized data management worldwide, offering unmatched flexibility, significant cost savings, and seamless scalability. However, this transformation also introduces a host of security challenges data theft, denial-of-service attacks, insider threats, misconfiguration errors, and malware infections all of which expose the limitations of traditional security approaches. This study explores how artificial intelligence (AI) can strengthen cloud security by leveraging machine learning, deep learning, natural language processing, predictive analytics, and automated incident response. To create a well-structured understanding of the intricate connections between security threats, AI-driven solutions, and protection strategies, an ontology has been incorporated into the proposed model. This integration not only enhances issue identification but also improves the assessment of AI-based defense mechanisms, leading to practical and effective security recommendations. By enabling early risk detection, swift attack responses, and reinforced data protection, this approach ensures a more resilient and secure cloud environment.