This research introduces an innovative GenAI approach to enhance regulatory compliance in the pharmaceutical industry. Faced with evolving FDA and EMA regulations, pharmaceutical companies struggle with manual, error-prone processes for updating internal documents. Our study proposes a two-step AI-driven solution to streamline regulatory update management. Step 1 employs semantic search to identify potentially impacted Standard Operating Procedures (SOPs) when new regulations are introduced. Step 2 utilizes a ReAct (Reasoning and Acting) agent powered by the GPT-4o model to perform detailed comparisons between regulations and each identified SOP, confirming impacts and pinpointing specific areas requiring updates. This automated system aims to reduce manual workload, minimize oversight risks, and ensure timely alignment with regulatory changes. The study demonstrates the potential of GenAI in transforming regulatory intelligence, offering a scalable solution to a critical industry challenge. Future work will focus on model refinement and real-world implementation to quantify benefits in time-saving and compliance accuracy.