The integration of artificial intelligence (AI) into cybersecurity has revolutionized the way organizations detect and respond to threats, but it also raises concerns about privacy protection. This article explores the challenges and benefits of leveraging safe and reliable AI systems in cybersecurity, emphasizing the importance of balancing effective threat mitigation with safeguarding sensitive information. Key AI applications such as intrusion detection, threat intelligence, and incident response are examined, showcasing how AI-driven data analytics can enhance real-time threat detection and improve overall security measures. The article also addresses the risks associated with AI, including adversarial attacks, data leakage, and the potential for misuse of automated systems, stressing the need for human oversight and robust security measures. Privacy-preserving techniques, including differential privacy and federated learning, are discussed as essential tools to protect data while leveraging AI technologies. Best practices for developing trustworthy AI systems are outlined, with a focus on privacy-by-design principles, regulatory compliance, and continuous monitoring to ensure that AI systems remain both secure and ethical. Through real-world case studies, the article demonstrates how organizations have successfully implemented AI-driven cybersecurity solutions that safeguard sensitive data, maintain user trust, and comply with privacy regulations. This article aims to provide organizations with a comprehensive framework for utilizing AI in cybersecurity while ensuring privacy protection.