The rapid evolution of Artificial Intelligence (AI) has transformed industries, enabling automation, data-driven decision-making, and enhanced efficiency. However, as AI systems grow increasingly sophisticated, they also introduce cybersecurity threats that endanger businesses, governments, and consumers. Cyberattacks targeting AI models, such as adversarial attacks, data manipulation, and algorithmic vulnerabilities, can compromise system integrity, cause financial losses, and harm organizational reputations. This paper examines cybersecurity challenges associated with AI-driven technologies, particularly their impact on business strategy and risk management. Key concerns like data privacy breaches, model poisoning, and AI-generated cyber threats are analyzed to assess their potential consequences across industries. From a business perspective, these risks demand proactive security measures, regulatory compliance, and robust risk mitigation strategies to ensure the safe and ethical deployment of AI. Drawing on case studies and industry insights, the study outlines effective approaches for securing AI applications, balancing innovation with security, and aligning cybersecurity frameworks with organizational goals. The findings highlight the importance of integrating AI-specific cybersecurity protocols into business strategies to build trust, resilience, and sustainable growth in an AI-driven global landscape.