# Artificial Intelligence in Aviation: New Professionals for New Technologies
## 1 Introduction  
The aviation industry is under increasing pressure to adopt artificial intelligence technologies (AI) to improve efficiency, safety, and competitiveness. Major aviation organizations have called for the implementation of AI to transform operations and address challenges.  
The rapid advancement and adoption of artificial intelligence technologies are fundamentally transforming the landscape of the aviation industry [1]. From flight planning to aircraft maintenance, AI-driven tools like machine learning, natural language processing, and computer vision are being integrated across nearly every aspect of modern aviation [2]. While AI innovation holds great promise for augmenting human capabilities and enhancing safety and efficiency, it also poses new challenges for aviation education and training. This paradigm shift requires aviation professionals to possess competencies in emerging technologies and their applications in order to be effective in increasingly AI-mediated work environments [3].  
This paper discusses the importance of re-evaluating and transforming aviation curricula, teaching methodologies, and learning outcomes to equip the next generation of aviation specialists with the knowledge and skills needed in an AI-driven industry. The integration of aviation and AI encompasses two key dimensions: using AI technologies within aviation systems and using AI in aviation education itself. Thus, developing appropriate AI competencies requires both conceptual knowledge of core AI concepts as well as applied skills in implementing and managing AI tools. Furthermore, aviation professionals must be cognizant of the ethical, legal, and social implications of relying on AI technologies for critical transportation operations and infrastructure.  
However, for the aviation sector to successfully integrate AI, there needs to be a sufficient talent pool of graduates with the required skills and knowledge. The research objective of the paper is the analysis of transforming aviation education for an AI-driven future. It is timely and important for two reasons. First, the aviation industry is looking to universities to produce graduates with AI competencies to fill the growing demand for AI skills. Second, for aviation programs to remain relevant and aligned with industry needs, they must evolve to include AI-related content that develops students' capabilities in this critical area.  
Through a review of current aviation training frameworks, analysis of industry workforce needs, and examination of best practices in AI education, this paper proposes core focus areas and competencies that aviation curricula need to integrate in order to produce graduates poised to enter an increasingly automated, intelligent aviation ecosystem. The insights from this study aim to provide guidance to aviation education leaders as they adapt their programs to the future of the industry. Equipping students with both specialized domain knowledge and new digital skills will be key to developing the next generation of aviation professionals [4].  
The study focuses on aviation engineering bachelor's programs at European universities because Europe has a large aviation industry and a strong higher education system. By analyzing program descriptions and syllabi, the research seeks to determine the extent to which AI-related topics such as machine learning, deep learning, computer vision, and natural language processing are incorporated. The findings will provide insights into how prepared European aviation graduates are for the AI transformation and what competencies are needed for the next generations of aviation professionals (NextGen) for the efficient operation of the next technologies of the aviation industry (NextTech) to produce the AI talents needed for the aviation sector.