Artificial intelligence (AI) integration in Unmanned Aerial Vehicle (UAV) operations has significantly advanced the field through increased autonomy. However, evaluating the critical aspects of these operations remains a challenge. In order to address this, the current study proposes the use of a combination of the 'Observe-Orient-Decide-Act (OODA)' loop and the 'Analytic Hierarchy Process (AHP)' method for evaluating AI-UAV systems. The integration of the OODA loop into AHP aims to assess and weigh the critical components of AI-UAV operations, including (i) perception, (ii) decision-making, and (iii) adaptation. The research compares the results of the AHP evaluation between different groups of UAV operators. The findings of this research identify areas for improvement in AI-UAV systems and guide the development of new technologies. In conclusion, this combined approach offers a comprehensive evaluation method for the current and future state of AI-UAV operations, focusing on operator group comparison.