Capacity Building for AI-Driven Qualitative Research in the Global South: Lessons from the Arab World

Introduction: Artificial intelligence (AI) is transforming the nature of qualitative research by facilitating automated transcription, coding, analysing, and data management. However, institutions and researchers in the Arab region face significant obstacles in adopting AI-driven technologies. This research explores how researchers in the Arab region perceive the incorporation of AI into qualitative research, with a particular focus on both opportunities and constraints for capacity building.

Goals and Methods: Employing an exploratory qualitative approach, this research will utilise a purposeful sampling technique to select university-based researchers from Oman, UAE, Egypt, KSA, and Jordan for semi-structured interviews. The research aims to explore one central question: How do researchers in the Arab region perceive the integration of AI into qualitative research? Interviews will be conducted both face-to-face and online in Arabic/English during September-October 2025. The final number of participants will be determined by reaching data saturation. The data collected will be analysed using a reflexive thematic analysis approach, facilitated by ATLAS.ti 25 for coding and analysis. To ensure the research's reliability and trustworthiness, the researchers will follow a structured process, provide detailed documentation, employ transparent coding procedures, and conduct member checking. Ethical approval for the research was granted, and informed consent will be obtained from all participants.

Results: The findings of this research are expected to shed light on issues related to AI tools and AI-driven qualitative research training. The findings will also provide insights into strategies for developing contextualised capacity-building programs tailored to researchers in the Arab region.

Conclusions: By highlighting the voices of researchers from the Global South, this research contributes to ongoing efforts to accelerate methodological innovations and improve epistemic justice in qualitative research.