Artificial Intelligence (AI) is transforming the landscape of safety-critical systems, from automotive to aerospace, and aviation applications. While AI has the potential to significantly enhance system performance and decision-making, its integration into regulated environments presents unique challenges. In safety-critical systems, where failure can lead to severe consequences, the need for rigorous, well-defined processes is paramount.

This presentation will focus on the role of AI in such systems, emphasizing the importance of transparency, validation, and verification in ensuring reliability, safety, and compliance with regulatory standards. We will explore best practices for designing and deploying AI models that adhere to stringent certification requirements, such as traceability, explainability, and continuous monitoring. Special attention will be given to how these processes can address the inherent uncertainties and complexities of AI, ensuring that safety-critical applications meet the highest standards of performance and regulatory oversight. By implementing structured processes, developers can leverage the power of AI to innovate while maintaining the required safety and integrity.