DOI: 10.1108/jices-10-2025-0287 ISSN: 1477-996X

Remote collaboration of employees reframed with the lens of AI efficiency, trust and ethical visions

Suman Kumar, Massoud Moslehpour, Ankita Manohar Walawalkar, Vimal Kumar

Purpose

This study aims to examine the impact of artificial intelligence (AI)-driven workflows on efficiency and collaboration, shaping employees’ attitudes and intentions. In addition, it theoretically contributes by linking AI adoption to different levels of collaboration, showing how trust and risk influence engagement.

Design/methodology/approach

This study conducted a survey with remote work employees in Indian information technology (IT) firms and received 386 respondents. The study further extended the unified theory of acceptance and use of technology (UTAUT2) model, and for a comprehensive analysis, partial least squares structural equation modeling using SmartPLS4 was used.

Findings

The study findings underline the significant impact of AI adoption on employees’ attitudes and intentions. Results also demonstrate how trust and risk perceptions determine the depth of collaboration in remote AI-enabled work environments. It further provides insights into how traditional job practices adapt to an AI-integrated work environment.

Research limitations/implications

Finally, this study contributes to understanding organizational adaptation in an AI-enabled environment and gives practical and managerial insights for organizational leaders, practitioners and policymakers while ensuring a trust- and ethics-focused AI system in remote work. The findings contribute to collaboration theory by empirically showing how trust enables, and risk constrains, effective collaborative engagement in remote work.

Originality/value

The rapid use of AI in remote work scenarios in Indian IT firms influences collaboration and work efficiency. However, this scenario is hindered by certain challenges related to stakeholder and employee trust and ethical concerns. This study provides a novel integration of UTAUT2 with collaboration frameworks, emphasizing the theoretical link between AI adoption, trust, risk and collaboration levels.

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