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This study provides a comprehensive investigation of the opportunities and challenges associated with generative artificial intelligence (GAI) use in development and learning in organizations. Additionally, it highlights the future avenues in GAI research and provides practical recommendations for policymakers.

Data for the review was collected from the Web of Science database using the search criteria (“Generative artificial intelligence” OR “artificial intelligence”) AND (“human resource management” OR “human resource development” OR “workplace learning” OR “organizational learning” OR “organizational development” OR “learning organization”) on March 6th, 2024. Filtering results to Management and Business categories yielded 71 articles. After abstract review, 6 unrelated articles were excluded, leaving 65 articles for final analysis.

The study presents several opportunities of GAI such as applications in personal learning and content generation. Moreover, it unravels several potential challenges of GAI such as quality and accuracy issues and elucidates several future research directions.

Our study is the first literature review that provides and a comprehensive overview of generative artificial intelligence in the context of organizational learning.

This study's objective is to give a thorough overview of the literature in the field of “quiet quitting.” This paper presents literature review on quiet quitting, analyzing its conceptual framework, antecedents, outcomes, and potential strategies for addressing this pervasive issue.

Using the keywords “quiet quitting” and “silent quitting” from the Scopus database, a systematic review of the literature was conducted, applying the Antecedents-Behaviour-Consequences (ABC) approach, popularized by B.F Skinner, to get a conceptual clarity of this topic. There were just twenty articles discovered in the search until October 15, 2023. This review was undertaken after full-text screening of relevant studies, which are duly cited. The literature review also revealed some themes that are discussed in the study.

The study identifies relevant “quiet quitting” definitions as well as potential individual and organizational-level causes using a descriptive and thematic review of the literature. Additionally, critical insights and research gaps that could be used for empirical studies are identified.

This study provides as a roadmap for organizations to proactively recognize and address concerns, resulting in enhanced workforce well-being and productivity.

The study could spur further research and serve as a resource for scholars interested in the concept of “quiet quitting,” as well as benefiting human resource managers who prefer evidence-based management.