The rapid advance of artificial intelligence technology has made it possible to use many different systems that utilize it. However, current Artificial Intelligence (AI) applications are vulnerable to attacks that can’t be detected, discriminating against groups that aren’t well represented, and don’t protect user privacy. These issues make use of Trustworthy AI (TAI) systems challenging and degrade users’ confidence in all AI systems. In this chapter, we focus on AI professionals’ complete roadmap to making AI systems that people can trust. This explores the most critical aspects of Trustworthy AI (TAI) and TAI technologies, revealing new insights, addressing knowledge gaps, and facilitating potential advancements, including fairness, transparency, explainability, accountability, robustness, and privacy protection. The newly developed approaches of AI, Machine learning (ML) algorithms, and Blockchain (BC) technology have gained attention to enhance the privacy and security of systems against threats. With the combination of AI and IoT, the Edge computing approach can improve user trustworthiness, security, and privacy. There are many advantages of AI in trustworthy AI devices, but despite that, the security threats are increasing progressively, which emphasizes the requirement for cybersecurity. Adopting end-to-end encryption and developing zero-trust architecture help the organization secure data.