Jul 2026· Digital Theory, Culture & Society· Vol 4· 0 citations· 56 references
TL;DR
An integrative conceptual framework linking algorithmic workplace practices, ethical challenges, and employee well-being, moderated by organizational support, AI transparency, digital capability, and ethical leadership is contributed, alongside a practical framework for implementing sustainable, human-centered AI governance in digital workplaces.
Abstract
The rapid expansion of AI-mediated workplaces has transformed digital work culture, reshaping how organizations manage, monitor, and evaluate employees. While AI-driven systems enhance operational efficiency and support data-driven governance, they also raise ethical concerns regarding surveillance, autonomy, fairness, and employee well-being. This study presents a Systematic Literature Review (SLR) using the PRISMA framework and thematic synthesis to identify and analyze 44 peer-reviewed articles published between 2015 and 2026 from six databases: Scopus, Web of Science, ScienceDirect, Emerald Insight, SpringerLink, and Google Scholar. The findings are organized into six themes: AI adoption in digital workplaces, employee trust in AI, ethical tensions in algorithmic decision- making, algorithmic management and workplace control, psychological well-being, and human-centered AI governance. The review shows that, despite improving organizational performance, AI-mediated systems contribute to technostress, burnout, AI anxiety, identity threats, and reduced worker autonomy. Key ethical concerns include algorithmic bias, opacity, discrimination, and inadequate institutional governance. This study contributes an integrative conceptual framework linking algorithmic workplace practices, ethical challenges, and employee well-being, moderated by organizational support, AI transparency, digital capability, and ethical leadership, alongside a practical framework for implementing sustainable, human-centered AI governance in digital workplaces.
Digital transformation constantly changes the work practices and employee experiences of contemporary work environments. Studies have documented the adverse impact of cutting-edge technologies, such as artificial intelligence, algorithmic systems, and digital platforms on employees’ well-being. However, such findings remain fragmented across technologies, disciplines, and well-being constructs, limiting a coherent understanding of how digitally transformed work conditions affect employees. This study systematically reviews the literature on digital transformation and employee well-being to clarify the conditions, mechanisms, and outcomes that are most consistently identified in prior research. Using the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) method, this study identified, screened, and selected 57 peer-reviewed articles (2014–2025) on digital transformation and employee well-being. The Gioia inductive analytical approach was used to synthesise the reviewed studies and to develop higher-order conceptual dimensions. Five interrelated aggregate dimensions were identified: digital transformation conditions, digital resources and demands, mediating processes, contextual factors, and employee well-being outcomes. The findings indicate that employee well-being depends significantly on how digitally intensified demands and available resources are configured, interpreted, and mediated within specific organisational contexts. This review highlights the need for more temporally sensitive, context-specific, and resource-oriented research, and proposes an integrative framework to guide future research and support the design of healthier and sustainable digital workplaces.
Sharmila Rani Moganadas, Gerald Guan Gan Goh, Chew Sze Cheah et al.· Societies· 0 citations
There is no denying that the rapid proliferation of digital oversight has transformed how organizations manage employee performance, offering new capacities for tracking activity and output while raising serious psychological and social concerns. This systematic literature review (SLR) synthesizes empirical and theoretical evidence on the effects of digital monitoring (DMon) on employees' trust, autonomy, and stress at work. Eighteen peer-reviewed studies published between 2009 and 2025 were critically reviewed following PRISMA guidelines, drawing on the psychology, management, and information systems literature. The search strategy was broadened beyond the original core terms to include "employee analytics," "algorithmic control," and "workplace digital tracking systems," which surfaced additional empirical evidence from gig-economy and algorithmic-management contexts and improved the geographic and methodological diversity of the final sample. Thematic synthesis identified three key themes: (1) a "surveillance–trust paradox," whereby surveillance intended to increase accountability instead erodes interpersonal and organizational trust; (2) autonomy frustration and psychological reactance, as surveillance constrains discretion and provokes efforts to reassert control; and (3) stress-related experiences and coping strategies, including emotional exhaustion, resistance behaviours, and adaptive self-monitoring. Taken together, the findings support the view that perceived intrusiveness and non-disclosure of monitoring threaten basic psychological needs and relational cohesion. Rather than treating Organizational Trust Theory, Self-Determination Theory, and Conservation of Resources theory as separate, parallel explanations, this review consolidates them around Social Exchange Theory (SET) as the single dominant integrative model: monitoring is interpreted as a signal within an ongoing exchange relationship, and it is through this exchange lens that autonomy frustration and resource loss acquire their stress-inducing meaning. A comparative appraisal of methodological quality across the 18 included studies is reported alongside the thematic synthesis. The review concludes that socially responsible surveillance grounded in transparency, participatory design, and ethical governance is key to reconciling organizational accountability with employee trust, autonomy, and well-being.
Laura Aghedo· International journal of res...· 0 citations
Purpose: Generation Z, the newest cohort entering the labour market, brings workplace expectations that differ markedly from those of earlier generations. This paper consolidates contemporary research to examine how Gen Z’s workplace expectations intersect with prevailing organizational cultures and to identify the organizational mechanisms most effective in supporting retention.
Design/methodology/approach: A thematic review of peer-reviewed studies published between 2020 and 2025 was conducted. A Scopus database search using the keyword “workplace expectation” returned 182 documents, which were screened in three stages to produce a final corpus of 59 papers. The selected studies were coded deductively in NVivo, guided by two research questions, and organized around three broad dimensions: HR policy adaptability, the integration of digital HRM practices, and sustainability-driven organizational methods.
Findings: The synthesis shows that Gen Z consistently expects flexibility and autonomy, continuous learning and meaningful work, open communication with supportive leaders, and value-based organizations that act on their ethical, diversity, and social commitments. These expectations reflect a changed psychological contract in which growth and purpose are basic conditions of engagement rather than rewards for loyalty. However, a persistent gap remains between these expectations and actual management practice, as many organizations still rely on top-down authority and rigid hierarchies, fuelling disengagement and turnover.
Practical implications: Organizations should shift from controlling to coaching leadership, build culture and psychological safety from onboarding onward, keep communication transparent, protect well-being and work-life balance, and offer fair, personalised rewards and continuous upskilling.
Originality/value: By synthesising a fragmented body of literature, the paper offers an integrated framework linking Gen Z expectations to organizational culture and human resource practice, along with directions for future longitudinal and cross-national research.
Nisha Pawaria· International Journal of Glo...· 0 citations
In digital transformation contexts, organizational change remains challenging especially when employee resistance is underestimated and change management efforts are fragmented. This study presents a systematic review on organizational change with a focus on resistance dynamics, change management frameworks, and the role of emerging technologies in technology-enabled transformation. Following PRISMA 2020 guidelines, 83 peer-reviewed articles were screened and analyzed using thematic and bibliometric approaches. This review integrates resistance to change, change management models, and digital transformation within a unified socio-technical perspective. The findings show that resistance is shaped by interrelated individual, organizational, and cultural factors. On the other hand, successful transformation is consistently associated with transparent communication, inclusive leadership, psychological safety, and cultural alignment. Moreover, the study shows that technologies such as gamification, AI-powered chatbots, and virtual and augmented reality can strengthen engagement, learning, and participation when embedded within broader change management processes. The bibliometric analysis identifies major intellectual trends, influential contributors, and emerging directions in the field. Overall, the study offers an integrated theoretical and practical foundation for understanding how human and technological factors jointly shape organizational change in digital transformation.
Ryan Alshaikh, Israa Al-Khafaf, Vian Ahmed et al.· International Journal of Eng...· 0 citations
Despite 72 percent of organizations adopting artificial intelligence, nearly half of implementations fail due to employee resistance, a paradox that challenges technology acceptance models. Prior research has examined either cognitive acceptance or motivational responses in isolation, leaving the interplay between these pathways and their ethical contingencies unresolved. This research addresses this critical gap through a sequential explanatory mixed-method design combining a quantitative survey of 1,785 employees in AI-adopting organizations with in-depth qualitative interviews with 19 participants, analysed using SmartPLS 4 for structural equation modelling and NVivo 14 for thematic analysis. The findings reveal three key insights. First, psychological empowerment mediates the relationship between technology characteristics and job satisfaction more strongly than technology acceptance, a counterintuitive finding that challenges the technology acceptance model's 30-year dominance. Second, job satisfaction emerges as the strongest predictor of organizational performance. Third, ethical leadership moderates both pathways, such that high ethical leadership amplifies empowerment effects by 34 percent. This research advances a novel Ethical Dual-Pathway Technology Acceptance Model (EDP-TAM), offering actionable guidance for organizations to implement AI that simultaneously optimises performance and safeguards employee well-being.
AI is rapidly transforming HRM, with organizations and universities adopting AI systems to recruit, evaluate, and analyse their workforces. While these technologies promise efficiency, flaws or biases in algorithms can affect individuals' careers and organizational performance, turning technological improvement into a matter of trust. Without proper governance, AI risks perpetuating bias and undermining accountability. Yet current research focuses largely on efficiency and cost savings, and the lack of integration between HRM and IT perspectives means organizations often implement AI without considering how governance structures and design decisions affect people. This study addresses that gap by investigating the governance of AI systems in HR through four questions: how governance structures shape trust, what role ethical frameworks play in mitigating bias, how system design influences transparency and accountability, and whether demographic and professional differences shape trust. Applying a socio-technical systems analysis to survey data from organizational and higher education participants, the findings show near-universal support for governance frameworks, with trust significantly associated with professional role, AI familiarity, and governance orientation.
Sapheya Aftimos, D. Hassoun· AHFE International· 0 citations