International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Technostress in AI-Augmented workplaces:A conceptual HR framework for employee well-being and organizational resilience

Author(s) Ms. Dishani B B, Ms. Anusha patige
Country India
Abstract AI and generative AI (GenAI) tools are spreading quickly through everyday work, changing how employees do their jobs, learn new skills, and get evaluated — and along with that comes a set of psychological pressures that most HR functions are not yet equipped to handle. Drawing on established technostress research and recent studies of AI-related anxiety, this paper builds an integrative conceptual framework connecting AI-specific technostress creators — techno-overload, techno-complexity, techno-invasion, techno-uncertainty, and algorithmic opacity — to employee well-being, engagement, and performance, with HR policy, digital upskilling, job redesign, and psychological-safety practices acting as the key organizational moderators. Drawing on peer-reviewed evidence from 2024–2026 across technostress, occupational health, and AI-adoption research, the paper identifies a gap: although the causes and health effects of AI-driven technostress are now fairly well documented, there is still little integrated guidance on how HR departments — particularly in emerging-market and services settings — can actually operationalize resilience-building interventions before, during, and after an AI rollout. A mixed-method research design combining a structured survey with semi-structured interviews across IT-enabled service organizations is proposed for future empirical testing of the framework. The paper closes with a practical HR action agenda covering AI literacy training, workload governance.
Keywords Technostress, Artificial Intelligence, Generative AI, Employee Well-being, Human Resource Management, Digital Resilience, Job Design, Organizational Support.
Field Business Administration
Published In Volume 8, Issue 4, July-August 2026
Published On 2026-07-28
DOI https://doi.org/10.36948/ijfmr.2026.v08i04.83720
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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