Understanding Stakeholders of Industrial AI: Insights from a Persona-Based Questionnaire
Yasin Ghafourian, Fabian Lindner, Olga Kattan, Konstantina N. Karathanasopoulou, Markus Tauber, George Dimitrakopoulos · 2025
The rapid evolution of industrial artificial intelligence (AI) has given rise to a diverse landscape of developers and users across various sectors. Understanding their personas—including their backgrounds, expertise, and work environments—is crucial for fostering innovation and ensuring compliance with AI regulations. This study presents insights from a persona-based questionnaire aimed at mapping the industrial AI ecosystem and informing the development of a user-centred self-assessment compliance tool. Through a structured survey of 61 participants from European AI research projects, the study identifies key attributes of AI professionals, their industry affiliations, and their approaches to AI adoption and compliance. Findings reveal gaps in awareness and application of AI guidelines, with half of the respondents uncertain whether their organizations follow formal AI standards. Moreover, AI familiarity influences risk perception, with experienced users more likely to identify algorithmic and resource-related challenges. The study integrates the Quantitative Effect and Technology Acceptance Model (QETAM) to assess chatbot acceptance for AI compliance support, ensuring the proposed tool aligns with user needs.