The growing dependence on cloud-hosted AI models opens up new dilemmas for IP protection since these models create invaluable investments in data, research, and expertise. Some key strategies aimed at AI model protection in cloud environments are discussed here, covering technical, legal, and operational perspectives for protecting IP. It points out the potential risks that could come about, including unauthorized access, reverse engineering, and data breaches. It analyzes various solutions to counter these, including encryption, access controls, watermarking, and confidential computing. The paper further discusses the legal frameworks necessary in terms of IP registrations, licensing, and NDAs, which legally protect these models and offer legal rights vis-à-vis the use of the model. The paper reviews the strategies of IP protection for organizations deploying AI in the cloud environment and provides real-world case studies to present a comprehensive understanding in this respect.