Data poisoning poses a significant existential threat to AI systems, compromising their integrity and trustworthiness. This cyberattack involves manipulating data to alter an AI's decision-making processes, leading to potentially catastrophic consequences. Organizations must prioritize AI system safety and invest in robust cybersecurity measures, including monitoring, anomaly detection, and regular audits. Failure to address this issue may result in severe repercussions, highlighting the urgent need for collective action to establish standards and regulations for AI accountability and safety.