As Large Language Models (LLMs) increasingly become integrated into critical industries such as health care, education, and finance, their susceptibility to adversarial attacks and the spread of disinformation has emerged as a significant concern. These AI-driven systems, while offering tremendous benefits like improved efficiency and decision-making, also present risks that can undermine trust and security. This paper delves into these challenges, focusing on the vulnerabilities of LLMs to adversarial manipulation and their potential role in generating disinformation. Using real-world case studies, including the UAE’s evolving AI landscape and international efforts to regulate AI, we demonstrate how such risks can lead to widespread disruption in vital sectors. In healthcare, for instance, adversarial attacks could compromise diagnostic tools, while in the financial sector, they could destabilize markets. Furthermore, disinformation spread by AI models, particularly through the rapid creation of false narratives, poses an additional threat to public trust and social stability. This paper offers a detailed analysis of current AI governance frameworks, from the UAE’s Cybercrime Law to the European Union’s AI Act, identifying critical gaps that need to be addressed. Our findings emphasize the necessity of more robust cybersecurity measures, globally harmonized policies, and collaborative governance structures to safeguard the future of AI. By fostering international cooperation, transparency, and accountability, we can ensure that the benefits of LLMs are realized while minimizing the risks posed by adversarial attacks and disinformation. Ultimately, this research provides a roadmap for policymakers, technologists, and global leaders to navigate the complex terrain of AI governance, security, and ethical considerations.