Adversarial Machine Learning (AML) is a critical field in artificial intelligence and cybersecurity, focusing on identifying vulnerabilities in AI systems and developing defenses against deceptive tactics that can cause these systems to make significant errors. As AI technologies become more integrated into daily life, the threat of adversarial attacks, which involve crafting inputs to mislead models, poses a serious challenge. This includes potential manipulation of both language models and computer vision systems. The evolution of adversarial tactics highlights the need for continued vigilance and innovative security measures, such as adversarial training, input validation, and real-time anomaly detection, to maintain the integrity and trustworthiness of AI systems. Key figures like Ian Goodfellow emphasize the importance of addressing these challenges to safeguard AI's role in society. Companies like Lakera are actively developing tools like Lakera Guard to protect against advanced adversarial threats, ensuring AI applications remain secure and reliable.