Published Paper Details:

The rapid advancement of digital technologies has significantly transformed modern computing environments, particularly through the integration of Artificial Intelligence (AI) with cloud computing. Cloud computing enables organizations to access scalable computing resources, storage, and services over the internet, eliminating the need for costly on-premise infrastructure. When combined with AI technologies such as machine learning, deep learning, and big data analytics, cloud platforms become powerful environments capable of processing massive datasets, generating insights, and supporting intelligent decision-making.This paper examines the evolution of AI cloud computing, beginning with early cloud infrastructure models and progressing through stages such as big data integration, machine learning adoption, and the development of AI-as-a-Service platforms. It also highlights the core technologies that enable AI cloud systems, including machine learning, deep learning, big data analytics, Internet of Things (IoT), and automated machine learning tools. The study further discusses the major benefits of AI cloud computing, such as cost efficiency, scalability, faster innovation, and improved data management.In addition, the paper explores key real-world applications across industries including healthcare, finance, transportation, smart cities, and e-commerce. While the adoption of AI cloud computing continues to grow, challenges such as data privacy concerns, cybersecurity risks, high data dependency, and technical complexity remain significant considerations.Finally, the paper outlines future trends shaping the next generation of AI cloud systems, including edge AI, intelligent automation, quantum computing integration, and advanced privacy-preserving technologies.