Despite growing investments, the widespread adoption and scalable deployment of
generative artificial intelligence (AI) remains a challenge due to data
trustworthiness, regulatory uncertainty, interpretability, and ethical
governance. The need to accelerate automation and maintain the human-in-the-loop
demonstrates broader questions of responsibility and transparency.
Next-gen AI for Aerospace Engineering investigates the transformative role of
GenAI within aerospace engineering, examining its shift from conventional
workflows toward more AI-driven solutions in design, manufacturing, and
maintenance. It emphasizes GenAI’s emerging ability to automate repetitive
mundane tasks, reduce design complexity, and optimize engineering pipelines. The
report underscores the need for validation methods that must align AI-generated
outputs with physics-informed models, integration with legacy engineering tools
(e.g., computational fluid dynamics, finite element analysis, digital twins),
and mitigation of algorithmic biases.