Search results

The 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.

Through 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.

The 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.

The 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.

While 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.

The COVID-19 pandemic found deliberate and idiosyncratic adoption of telecommuting and other flexibility practices across industries. With the pandemic waning, many organizations adopted various models for employee work locations. Based on Self-Determination Theory and Social Comparison Theory, the authors examine the impact of the dissonance between employee preference for their work location and enforced work location norms and its impact on general well-being and organizational commitment.

The authors’ empirical study is based on a sample of 881 respondents across multiple industries in India over six months of the COVID pandemic. The authors use PLS-SEM for data analysis to examine the model and the moderating influence of individual resilience on control at work.

The authors find that increased dissonance between work locations reduces general well-being, control and work. Further, higher individual resilience reduces the impact of this dissonance on control at work.

The study informs policy and practices that choice of work location is important for employees to feel a higher sense of control, impacting their affective commitment and general well-being. While implementation of policies across an organization for varying job roles and complexities presents a challenge, practitioners may ignore this need of employees at their peril, as employees are likely to demonstrate lower well-being, engagement and organizational commitment and eventually leave.

This study is significant as it provides relevant scholarship based on the COVID-19 pandemic, guiding practice on future ways of working. This study further supports the impact of an individual's sense of control on where work is done. The authors build a strong theoretical foundation to justify the impact of the lack of autonomy in the emerging working norms on employees' general well-being and organizational commitment.