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The importance of mental wellbeing and the need for organizations to address it is increasing in the post-pandemic context. Although Artificial Intelligence (AI) is increasingly being adopted in HRM functions, its adoption and utility for enabling mental wellbeing is limited. Building on the Open System Theory (OST) and adopting the technology-in-practice lens, the authors examined the roles of human and technology agencies in enabling mental wellbeing.

The study was conducted in two stages; in Stage 1, the authors adopted a case methodology approach to examine the feasibility of a technology company's offerings to assess mental wellbeing. In Stage 2, the authors followed the grounded theory approach and interviewed 22 key stakeholders and HR leaders of diverse organizations. The authors used Gioia's approach to analyze the data.

The study demonstrates the interdependence and inseparability of human activity, technological capability and structured context. Specifically, the authors observe that AI adoption is pushing the boundaries of how organizations could support employees' mental health and wellbeing. These technological advancements and adoption are likely to facilitate the evolution of agentic practices, routines and structures.

This study carries two important implications. While the advent of cutting-edge technologies appears to affect employees' mental wellbeing, the study findings indicate the assistive role of technology in supporting mental wellbeing and facilitating changes in organizational practices. Second, the ontology of technology-in-practice shows how human–machine agencies gain newer relevance from the interactions that unite them. Specifically, per OST, technology (from an external context) can potentially change how mental wellbeing practices in organizations are managed. The authors extend the existing literature by suggesting that both human agents and internal contexts effectively limit the potential of technology agents to change existing structures significantly.

The authors address the need for more research on the technology-management interface, and the boundaries of technology-enabled wellbeing at work. While AI-HRM scholarship has primarily relied on micro-level psychological theories to examine impact and outcomes, the authors borrow from the macro-level theories, such as the OST and the technology-in-practice to explain how AI is shifting the boundaries of human and machine agencies for enabling mental wellbeing.

Because employees’ positive attitudes and behaviors are important to ensure organizational performance, organizations attempt to carry out human resource practices to shape these attitudes and behaviors. This paper aims to examine this issue by focusing on the effects of training and development (TD) on employee engagement (EE), satisfaction (ES) and retention (ER).

For empirical analysis, the authors use structural equation modeling and data collected from employees in a developing economy.

TD is positively and directly associated with EE, ES and ER. In addition, EE is found to mediate the indirect effects of TD on ES and ER.

The findings suggest some practical implications for TD activities to enhance employees’ positive attitudes and behaviors.

To the best of the authors’ knowledge, this research is among the early attempts to examine the direct and indirect effects of TD on EE, ES and ER in a developing economy. The findings add to the growing literature suggesting that TD can contribute to the improvement of employees’ positive attitudes and behaviors.