When HRD qualitative evidence speaks in the era of AI: an insight into Smart Quality Criteria (4Cs) for rigorous validation

This paper aims to develop Smart Quality Criteria (4Cs) for students and researchers in human resource development. This work is designed not only to support the trustworthiness of qualitative enquiry but also to emphasise the importance of validation and reliability by integrating AI technologies to achieve high-quality standards in qualitative research. Smart Quality Criteria (4Cs) are ethical check, data check, analytical check, and findings interpretation check, which can be used for rigorous validation. These new criteria indicate that the number of interviews in any research project and other key elements within the quality criteria should be determined. This work is positioned as a policy-oriented research statement, focusing on conceptual and strategic insights rather than empirical analysis. The study’s contribution and its theoretical, practical, and methodological impacts are also discussed. It also offers guidance on how HRD researchers can leverage existing and future AI technologies to enhance trustworthiness through strategies that strengthen the credibility and accuracy of qualitative results.