The aviation design process, often structured around the V-model, provides a systematic approach to developing complex systems such as an aircraft. This process progresses through requirement definition, system architecture design, implementation, integration and verification. Figure 1 shows the allocation of text-intensive design stages like documentation of system specifications, interface definitions, and safety analyses. In contrast, later phases, particularly software development, simulation modelling, and testing, are code-intensive[1].

Automation plays a crucial role in meeting these certification requirements, with advancements in modeling and simulation, automated code generation, and test automation enhancing efficiency and reliability. AI and machine learning contribute to design optimization, compliance verification, and error detection, while Retrieval-Augmented Generation (RAG) models[2] can facilitate knowledge retrieval from technical documents, regulatory guidelines, and test reports. However aerospace engineering is heavily influenced by stringent certification standards such as DO-178C (Software Considerations in Airborne Systems and Equipment Certification)[3] and ARP 4754A (Guidelines for Development of Civil Aircraft and Systems)[4]. These standards enforce rigorous requirements for software implementation and verification to ensure safety. Additional requirements to maintain compliance with norms for the application of process automation tools, such as DO-330 (Tool Qualification)[5], particularly when dealing with non-deterministic systems like Generative AI, introduce further challenges.

This paper explores the impact role of role of Generative AI-driven tools such as RAG in supporting automation in systems engineering. The authors will guide the reader through each phase of the V-model, examining key stages such as requirements definition, implementation, integration and testing. A detailed discussion will also be dedicated to the compliance of Generative AI based tools to qualification norms and certification norms.

References

[1] X Seabridge, Allan. G.; Moir, Ian: Design and development of aircraft systems. 3rd edition. John Wiley & Sons Ltd (2020), p18.

[2] Xiao, Tong and Jingbo Zhu. “Foundations of Large Language Models.” (2025), p12.

[3] DO-178C. Software considerations in airborne systems and equipment certification. RTCA.

[4] ARP4754A. Guidelines for Development of Civil Aircraft and Systems, SAE.

[5] DO-330. Tool Qualification. RTCA.