I study how cultural values shape the use and understanding of ethical AI in Qatar’s public sector. I also look at how knowledge moves inside these organisations. Who collects it? Who shares it? How it turns into decisions. I draw on three areas: knowledge management and acquisition, cultural studies, and locally grounded AI ethics. Together, these strands help me show something simple and practical. Culture influences technology choices, and it also influences whether people trust AI or push back against it.
Knowledge Management and Knowledge Acquisition
The KM literature explains how organisations handle what they know. Pérez‐Nordtvedt et al. (2008) point to four markers of effectiveness: comprehension, usefulness, speed, and economy. Zahra et al. (2000) add three angles on learning: breadth, depth, and speed, linking them to adaptation and innovation. Bjorvatn and Wald (2020) bring in people and pressure. Trust and time matter. In Qatar’s public sector, I want to see if these same forces shape how AI-related knowledge is effectively acquired. Does hierarchy slow the flow? Does caution keep people from sharing or experimenting? I will test these models against local practice, where authority and comfort with uncertainty play different roles.
Cultural Dimensions and Organisational Behaviour
Hofstede’s (2013) and GLOBE’s (2025) models are common tools for individual cultures. I will study these cultures, for example, Power Distance and Uncertainty Avoidance, to explore the impact of these cultures on knowledge acquisition. GLOBE’s views on collectivism and performance orientation, for instance, help explain how group expectations drive accountability. I will not treat these models as universal rules, as they were built on Western samples. I want to see where they fit and where they miss in Qatar’s institutions. This aligns with Al-Alawi et al. (2007) and Jiacheng et al. (2010), who show how trust and motivation shape cross-cultural knowledge sharing.
Ethical AI and Cultural Alignment
Recent studies by Özkan (2025), Kladko (2023), and Shin et al. (2022) argue for ethics that match local norms. Not a single global template, and of course, local values matter. In Qatar, these points toward community-oriented reasoning and collective responsibility. Cannavale et al. (2025) show that AI develops differently across countries, which supports a comparative approach rather than one standard model. My goal is to build an AI governance approach that works for Qatar’s governmental organisations and reflects its culture.
Where the Literature Falls Short
When I started this project, one thing I found out is that working from the Middle East on culture and AI reliance in public organisations is rare. Most studies look at Western or East Asian contexts. That gap pushed me to look closer. In this research, I connect knowledge management, culture, and ethical AI to shape a model suited to Qatar. The aim is practical. If you respect people’s cultural values, AI governance becomes fairer, more stable, and easier to trust.
References
Hofstede (2013); GLOBE Project (2025); Pérez‐Nordtvedt et al. (2008); Zahra et al. (2000); Bjorvatn & Wald (2020); Al-Alawi et al. (2007); Jiacheng et al. (2010); Özkan (2025); Kladko (2023); Shin et al. (2022); Cannavale et al. (2025).

Nov 10, 2025