Generative AI in Cloud Environments: Opportunities and Limitations

Abstract

Generative Artificial Intelligence (AI) has rapidly evolved into one of the most transformative technologies of the digital era, enabling automated content creation, intelligent decision support, and enhanced human–machine collaboration. Its integration with cloud computing environments opens new opportunities for scalability, accessibility, and enterprise adoption across diverse industries. By leveraging cloud infrastructures, organizations can deploy generative AI models at scale, reduce infrastructure costs, and foster innovation in areas ranging from healthcare to education, cybersecurity, and creative industries. However, despite these opportunities, limitations remain significant, including computational overhead, data privacy risks, model interpretability challenges, and concerns about bias and ethical misuse. This paper explores the intersection of generative AI and cloud environments, analyzing the benefits of scalability, collaboration, and innovation alongside the constraints of technical, ethical, and governance-related barriers. The study concludes with insights on how enterprises and policymakers can harness generative AI in the cloud responsibly and sustainably.