Adverse media screenings are becoming increasingly popular as companies seek to proactively review negative news to safeguard their reputation and comply with regulations. However, simple search methods often result in too much irrelevant information, known as false positives, which can compromise the effectiveness of screening programs. Artificial intelligence (AI) tools such as Thomson Reuters CLEAR Adverse Media offer a solution by using natural-language processing (NLP) to more accurately identify relevant media mentions. These AI-driven tools save time and reduce human bias, making it easier for risk management teams to prioritize and categorize data. Machine learning (ML) technology further improves the effectiveness of these screenings by learning from experience and identifying false positives. While these tools are advanced, they still require some manual processing and configuration by corporate risk and compliance teams. The use of AI-driven adverse media screenings can help companies maintain regulatory compliance and identify potential financial and strategic risks, providing necessary tools to access relevant information and conduct comprehensive investigations. These developments, such as CLEAR Adverse Media, have been well-received by compliance officers and investigative teams for their ability to save time and reveal critical information that may have been missed with traditional search methods.