Pullaiah Vutla, Triveni Yenugu
The introduction of Generative Artificial Intelligence (GenAI) into the world of enterprise Software-as-a-Service (SaaS) is a crucial development in digital transformation. As one of the highest-performing applications of large language models (LLMs) to productivity software, Microsoft 365 Copilot is a product that promises productivity-level efficiency to increase but at the same time presents a difficult compound pose on the security and privacy issue. The paper has used a secondary qualitative study to review the threat climate of Copilot, privacy-leakage threats, and governance. The study uncovers several vectors of concern by combining technical documentation evidence, regulatory frameworks, and previous scholarly research that the focus of AI-based prompt injection, unintentional data synthesis, and accidental cross-tenant exposure. Findings indicate that Microsoft Purview, Data Loss Prevention (DLP), and Role-Based Access Control (RBAC) offer basic protection but are not very effective against moving GenAI workflows that constantly consume and recreate sensitive enterprise data. As can be seen, a comparison with Google Workspace Duet AI and Salesforce Einstein shows that the risks are not specific to any platform but are common to all SaaS environments that are augmented by AI. The article summarizes that AI-conscious and holistic governance strategy, consisting of technical, organizational, and regulatory controls, is the key to reducing the vulnerability of the enterprise level, as well as maintaining the productivity gains of GenAI integration.