Human Resource Development Review

The current study aims to present and synthesize extant studies across various fields that have discussed the use of generative artificial intelligence (GAI) in instructional procedures or processes. This study adopted the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model since it is the most widely used instructional and training design model. An integrative literature review of 71 articles was conducted as the primary methodology. We analyzed and summarized information about (a) the integration and implementation of GAI in each stage of the ADDIE model and (b) suggested uses of GAI based on the model to further leverage what it can offer. Potential ethical concerns and recommendations are also examined for future research and practice using GAI in ADDIE. The study concludes with a discussion and implications for future research and practice.

This study used race consciousness and Indigeneity as a conceptual lens to examine the current state of research in the field of human resource development (HRD) pertaining to the racialization of Black, Indigenous, and other People of Color (BIPOC). The findings revealed significant disparities across HRD journals that publish this content. An analysis of 53 peer-reviewed articles also uncovered recurring themes, with leadership emerging as the most prevalent, and issues related to higher education on the rise. Numerous studies discussed HRD’s (potential) role and contribution to racial reform as well. Consequently, we suggest the problem is not the absence of research on how racialization operates within our communities and organizations, but perhaps the nominal dissemination and visibility of such scholarship within HRD graduate education. Other implications of this study exposed gaps in theory-building research and raised concerns surrounding the criticality needed to support Indigenous-informed studies within HRD.

Advancements in artificial intelligence (AI) signal a significant shift toward more automated and data-driven workplaces, emphasizing the need for Human Resource Development (HRD) to prepare the workforce with adequate AI competencies for AI-empowered environments. AI policies and initiatives play a crucial role in providing the frameworks and actions that guide HRD efforts. In this study, we analyzed education and workforce policies in national AI strategies (NAISs) from 50 countries to delineate educational policy priorities, strategies, and support resources for developing an AI-competent workforce. Our analysis revealed that only 13 countries demonstrated high-level prioritization with clear objectives and comprehensive measures, primarily developed economies in Europe. We identified six categories of educational and training strategies focused on AI talent preparation and workforce reskilling. Additionally, four types of support resources were highlighted as key investments to enhance the success of these educational and training strategies. The findings have significant implications for HRD practice, particularly in designing and implementing AI-focused, workplace-oriented, and inclusive HRD curricula, programs, and policies that consider contextual and cultural factors. The results suggest the need for further HRD education research to explore emerging theories, AI workforce training models, pedagogical strategies, and the impact of contextual and cultural elements on workforce competency development.