AI as a shield against cyberattacks - employee awareness in the EU

The increasing sophistication of cyber threats has driven enterprises to adopt artificial intelligence (AI) as a key component of cybersecurity strategies. This study explores user perceptions of AI-driven cybersecurity solutions by applying the Kano model, marking the first stage of a broader investigation into AI effectiveness in cyberattack prevention. The research was conducted through a large-scale survey in Poland, Germany, Sweden, and Hungary, collecting 26,314 responses to assess how users classify various AI security attributes. The Kano model enabled the categorization of AI functions into must-have, one-dimensional, and attractive attributes, highlighting which AI-driven security features are deemed essential and which enhance user satisfaction. The findings indicate that real-time threat detection, automated risk assessment, and AI-based authentication are considered critical, whereas AI-driven security education and adaptive learning mechanisms, while valued, are not yet universally expected. The study also identifies concerns related to excessive AI monitoring and algorithmic bias in cybersecurity decision-making. These insights provide a foundation for further research into optimizing AI-based security frameworks and enhancing user trust in autonomous cybersecurity systems.