Trust is a foundational requirement for the widespread adoption of AI and generative AI technologies. This session explores how trust in AI has evolved, highlighting key milestones and the growing complexity of modern AI models. We will look at real-world challenges, such as the difficulty of understanding how AI makes decisions and the risks of bias in these systems. Real-world examples will be used to highlight ethical and transparency issues, alongside proposed strategies for safeguarding trust through robust validation and accountability measures in AI systems. Future prospects for enhancing AI trustworthiness will also be explored.