Aug 2026· Journal of Information, Communication and Ethics in Society· pp. 1-23· 0 citations· 59 references
TL;DR
This study provides a novel integration of UTAUT2 with collaboration frameworks, emphasizing the theoretical link between AI adoption, trust, risk and collaboration levels, and contributes to collaboration theory by empirically showing how trust enables, and risk constrains, effective collaborative engagement in remote work.
Abstract
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.
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.
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.
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.
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.
The results show that AI use for work exerts the strongest positive impact on employees' behavioral engagement, followed by emotional and cognitive engagement, and both human-like and functionality trust in AI positively moderate the relationship between work-related AI and behavioral engagement.
Liang Ma, Zhihao Qi, Xin Zhang et al.· Internet Research· 0 citations
As more and more AI-powered tools and platforms are adopted in organizations to automate routine tasks, support decision-making, and improve efficiency, adoption is often lopsided, with employees embracing the system while also wondering whether it can effectively perform work-critical tasks. This study examines how organizations adopt AI platforms by applying the Unified Theory of Acceptance and Use of Technology (UTAUT) in the context of user experience (UX) and competence trust, two AI-salient concepts. Competence trust is the extent to which employees believe an AI platform will reliably produce accurate, dependable, and work-relevant outputs. An exploratory sequential mixed-methods design was employed to generate and confirm inductive analysis-level explanations of trust formation and acceptance, grounded in insights gained through observation. The first phase involves semi-structured interviews with 15–25 organizational users. In this phase, the study maps the path from the UX stage to trust or distrust and acceptance, identifies important incidents that affect people's confidence in the platform, and gathers users’ trust-related language to help fine-tune constructs and measurement criteria. In Phase 2, a survey instrument is developed from issues identified in Phase 1 and established scales. CFA and SEM test a longer UTAUT model in which factors affecting performance expectancy, effort expectancy, social influence, and facilitating conditions are used to quantify levels of competence, trust and behavioral intention to use the AI platform. Where the sample size allows, multi-group comparisons can be made by user intensity or job function. Phase 3 combines qualitative themes and quantitative path findings through a combined display to extract converging data, identify contradictions, and provide expanded interpretations, ultimately deriving actionable suggestions that will be applied. Contribution of the study. The study contributes theoretically by framing competence trust as an integral mechanism linking UX to adoption within a broader UTAUT framework, and by providing a better explanation of why perceiving usefulness and ease of use alone may be inadequate in AI settings. Moreover, it has practical design and governance implications for organizations to foster sustainable adoption by incorporating UX features that signal reliability (e.g., stability, clear guidance, robust error handling) and by reinforcing social and organizational support to enhance trust.
The findings of this study could help bank executives, human resource managers, and policymakers understand the importance of human-focused implementation of AI, ongoing AI skill-building, and favorable organizational practices that boost employee satisfaction and innovation.
Assessing the effects of technology reliability (RL), credibility (CR) and technical competence (TEC) on HR professionals’ trust and, subsequently, their intent to deploy AI tools reveals that technology RL, CR and TEC each enhance trust in AI.
R. Arora, Neha Kumari Siradhana· South Asian Journal of Human...· 0 citations
This study investigates how organizational members concurrently perceive the benefits of artificial intelligence (AI) for knowledge management processes (KMPs) and the challenges involved in implementing AI within knowledge management systems (KMSs). Based on survey data from 378 respondents across diverse sectors and roles, the research employs validated instruments measuring perceptions of AI’s contribution to knowledge acquisition, documentation, sharing, and application, as well as perceived human, technological, financial, and ethical‑regulatory barriers. The results show a consistent positive relationship between perceived AI usefulness and perceived implementation barriers: individuals who attribute greater value to AI-enhanced knowledge processes also express heightened awareness of the complexities required to integrate AI into organizational systems. Knowledge documentation presents the strongest associations with all barrier categories, while knowledge sharing exhibits the weakest. Human‑related barriers emerge as the most pervasive across all processes, indicating the central role of employee readiness and organizational culture in shaping AI-enabled KM. These findings reveal a dual perception in which optimism regarding AI’s potential coexists with recognition of the organizational adjustments it demands. The study contributes to a more integrated understanding of AI adoption in KM, emphasizing that effective implementation requires aligning technological capabilities with human, cultural, and governance considerations.
M. Nakash, E. Bolisani· European Conference on Knowl...· 0 citations
The rapid development of artificial intelligence (AI) tools has increased productivity and enhanced the quest towards sustainable development goals (SDGs). Extensive research has focused on AI technologies and organizational performance in the private sector. However, research in the public sector and the willingness to embrace AI are underexplored. This study explores employees’ AI tolerance in a digitalized economy.
The study employs data from employees in Ghana’s public organizations and uses the partial least squares structural equation modeling to make in-depth analysis.
The results revealed that perceived usefulness positively influences willingness to embrace AI, while perceived ease of use correlates positively with both attitude and willingness to embrace AI. Moreover, job relevance and job security were positively associated with attitudes and willingness to embrace AI. Trust in AI emerged as a crucial determinant, positively influencing attitudes and willingness to embrace AI. Technological anxiety did not demonstrate a statistically significant relationship with either attitudes toward AI or willingness to embrace AI technologies.
It is necessary to foster positive attitudes and trust in AI, as well as address job relevance and security concerns, to facilitate the successful adoption and integration of AI technologies into various organizations.
The study provides new evidence on how to balance technological advances and human acceptance for organizational effectiveness, especially in a developing economy.
Bright Obuobi, Chen-Guang Liu, Faustina Awuah et al.· Employee Relations: The Inte...· 0 citations
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