The rise of AI-powered collaboration tools and digital surveillance systems is radically transforming the workplace- amplifying productivity yet raising ethical dilemmas and trust concerns. This study proposes a comprehensive conceptual framework titled "Tech-Augmented Trust", which investigates how organizations can foster employee trust in the context of increasing technological oversight.
Grounded in multidisciplinary literature spanning organizational behaviour,information systems, and digital ethics, the model examines key constructs such as AI collaboration, digital surveillance, psychological safety, ethical leadership, perceived autonomy, and organizational transparency. It further explores how these elements interact to influence outcomes like employee engagement, innovation, and retention intent.
A quantitative research design is proposed for empirical validation, leveraging structural equation modeling (SEM) on data collected from digitally mature organizations. The study aims to advance theory on trust in digital contexts and offer actionable insights for leaders seeking to ethically deploy AI and surveillance technologies while safeguarding the human element. This study offers a validated framework for balancing AI adoption and employee trust
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