The purpose of this exploratory study is to look into the necessity for Privacy-Preserving Artificial Intelligence (AI) in secure data sharing in the context of cybersecurity. The research design includes a comprehensive examination of the current literature and a survey questionnaire with industry professionals. The findings show a growing demand for privacy-preserving AI solutions in cybersecurity, driven by increased data privacy rules and the escalation of data breaches. The study found that typical data-sharing mechanisms frequently reveal sensitive information, rendering them inappropriate for handling secret data. The practical ramifications of these findings are substantial. They highlight the importance of enterprises implementing privacy-preserving AI solutions to improve data security while adhering to privacy standards. Such solutions can assist firms in leveraging their data for insights while maintaining the privacy of individuals' information. However, the study does identify shortcomings. The adoption of privacy-preserving AI systems can be difficult due to their computational cost and the potential decrease in data value caused by extra noise for privacy preservation. Furthermore, a lack of awareness and comprehension of these solutions among businesses creates additional hurdles to their implementation. The study underlines the critical need for Privacy-Preserving AI for secure data exchange in cybersecurity and advocates for increased awareness and research in this area to address the stated problems.