The machine/human agentic impact on practices in learning and development: a study across MSME, NGO and MNC organizations

• Published in: Personnel review Vol. 53; no. 3; pp. 791 - 815
• Main Authors: Dutta, Debolina, Kannan Poyil, Anasha
• Format: Journal Article
• Language: English
• Published: Farnborough Emerald Publishing Limited 13.05.2024; Emerald Group Publishing Limited
• Subjects: Artificial intelligence; Behavior; Dependency theory; Digitization; Explicit knowledge; Human capital; Human resource management; Knowledge management; Social exchange theory; Strategic management; System theory; Technology adoption; Training; AI adoption; Artificial intelligence (AI); Open systems theory (OST); Learning and development (L&D); Technology-in-practice
• ISSN: 0048-3486; 1758-6933
• DOI: 10.1108/PR-09-2022-0658

PurposeThe importance of learning in development in increasingly dynamic contexts can help individuals and organizations adapt to disruption. Artificial intelligence (AI) is emerging as a disruptive technology, with increasing adoption by various human resource management (HRM) functions. However, learning and development (L&D) adoption of AI is lagging, and there is a need to understand of this low adoption based on the internal/external contexts and organization types. Building on open system theory and adopting a technology-in-practice lens, the authors examine the various L&D approaches and the roles of human and technology agencies, enabled by differing structures, different types of organizations and the use of AI in L&D.Design/methodology/approachThrough a qualitative interview design, data were collected from 27 key stakeholders and L&D professionals of MSMEs, NGOs and MNEs organizations. The authors used Gioia's qualitative research approach for the thematic analysis of the collected data.FindingsThe authors argue that human and technology agencies develop organizational protocols and structures consistent with their internal/external contexts, resource availability and technology adoptions. While the reasons for lagging AI adoption in L&D were determined, the future potential of AI to support L&D also emerges. The authors theorize about the socialization of human and technology-mediated interactions to develop three emerging structures for L&D in organizations of various sizes, industries, sectors and internal/external contexts.Research limitations/implicationsThe study hinges on open system theory (OST) and technology-in-practice to demonstrate the interdependence and inseparability of human activity, technological advancement and capability, and structured contexts. The authors examine the reasons for lagging AI adoption in L&D and how agentic focus shifts contingent on the organization's internal/external contexts.Originality/valueWhile AI-HRM scholarship has primarily relied on psychological theories to examine impact and outcomes, the authors adopt the OST and technology in practice lens to explain how organizational contexts, resources and technology adoption may influence L&D. This study investigates the use of AI-based technology and its enabling factors for L&D, which has been under-researched.