2026· International Journal of Management Studies and Social Science Research· 0 citations· 24 references
TL;DR
It is argued that digital empathy is best conceptualised as a relational interface that complements—rather than replaces—human connection that complements—rather than replaces—human connection.
Abstract
This paper examines the evolving role of artificial intelligence (AI) in supporting employee well-being through mechanisms of digital empathy. Drawing on qualitative case studies of two global organisations deploying AI-based emotional support systems, the research investigates how employees interpret and interact with these technologies. The study is guided by three core questions: How is empathy simulated through AI in workplace settings? How do employees perceive and experience these systems? What ethical and relational dynamics shape their implementation and impact? A qualitative multi-case design was adopted, utilising semi-structured interviews with HR professionals and end users (n=22) and document analysis of platform architecture and language models. Findings reveal that while AI systems can provide emotionally responsive feedback, users remain ambivalent about their authenticity and ethical use. Participants valued the immediacy and privacy of AI-based tools but highlighted limitations in nuance, trust, and cultural fit. Drawing on emotional labour theory and self-determination theory, the paper argues that digital empathy is best conceptualised as a relational interface that complements—rather than replaces—human connection. Organisations must embed these tools within cultures of psychological safety and ethical transparency. The study recommends participatory co-design of well-being technologies and hybrid models of care that preserve emotional authenticity. These insights contribute to emerging debates on AI, care work, and the transformation of human resource management in the algorithmic age.
Artificial intelligence tools that detect, infer or simulate emotion are rapidly entering the leadership toolkit, promising earlier detection of burnout, personalised check-ins and scalable care. Yet when empathy is increasingly mediated by algorithms, core relational qualities of leadership—authenticity, trust and psychological safety—can be put at risk. This paper explores the dark side of AI-enabled empathy by conceptualising an algorithmic empathy–authenticity gap: a disconnect between the growing volume and precision of empathetic signals and employees’ sense that those signals are genuinely felt and humanly owned. We identify four mechanisms that widen this gap—predictive emotional surveillance, synthetic emotionality, empathy inflation and relational displacement—and show how each reshapes emotional labour and leader–employee relationships. Building on these mechanisms, the paper outlines governance and design strategies that position AI as assistive rather than substitutive, safeguard emotional privacy and deliberately reconnect employees to human support. The argument reframes empathetic leadership as a socio-technical practice in AI-rich workplaces.
Anurag Tiruwa, Shuchi Dikshit· International Journal of Man...· 0 citations
As organisations increasingly embed artificial intelligence (AI) into the routines of leadership, from predictive performance dashboards to AI-assisted feedback and coaching tools, a pressing but underexamined question is how this technological augmentation of leadership shapes employees' willingness to speak up. This paper develops and defends a conceptual model in which AI-augmented leadership predicts employee voice behaviour through two theoretically distinct but interlocking psychological mechanisms: trust in the combined leader-AI system, and psychological empowerment. Drawing on social exchange theory) the integrative model of organisational trust, Spreitzer's theory of psychological empowerment, and the growing empirical literature on trust in artificial intelligence, the paper argues that AI-augmented leadership is neither inherently emancipatory nor inherently silencing; its consequences for voice depend on whether it is experienced by employees as a resource that expands judgement and relational engagement or as a mechanism of algorithmic control that narrows it. The paper further situates trust and empowerment within the longer-standing voice literature on psychological safety and implicit theories of self-censorship, showing how these established constructs sharpen, rather than duplicate, the proposed model. Five research propositions are advanced, a boundary condition involving AI transparency is specified, and a research agenda for empirically testing the model is outlined. The paper contributes to the emerging literature on AI and leadership by reframing the central question from whether AI replaces leaders to how leaders' use of AI is interpreted by employees, and by clarifying the specific psychological pathways through which that interpretation either encourages or forecloses constructive dissent.
Kingsley I. Amadi· Journal of Management Resear...· 0 citations
Artificial intelligence is being adopted in educational settings faster than its consequences are understood. We argue that the central risk is misalignment: AI that eliminates human effort erodes the very capacities education is meant to build. We organize this risk into an integrative framework of four interrelated dimensions -cognition, agency, emotional well-being, and ethics- linked by a self-reinforcing cycle where cognitive offloading reduces effort, weakens agency, and compounds emotional and ethical harm. We ground the framework in the perspective of a small cohort of students: an exploratory analysis of 49 International Baccalaureate argumentative essays about the impact of AI reveals that learners perceive these risks, with $80\%$ of essays reporting that AI reliance reduces thinking. At the same time, the essays articulate a consistent vision of the AI the students want: systems that support rather than replace learning by withholding immediate answers, prompting recall, and encouraging reflection through questions instead of solutions. These desiderata closely align with established principles from the learning sciences. Building on these insights, we propose a single design principle, scaffold, do not substitute. We argue that this principle extends beyond education. It represents a broader challenge for the AI ecosystem: any system that mediates human thinking can either weaken human capabilities through substitution or strengthen them through scaffolding. We conclude by outlining a research agenda for developing AI systems that foster enduring human capacity, an imperative not only for learners but, ultimately, for democratic societies.
Lucile Favero, J. A. Pérez-Ortiz, Tanja Käser et al.· 0 citations
This study examines how adolescents perceive emotional support from human and AI therapists in a therapeutic context and recommends an ethical hybrid framework that integrates AI into therapeutic support while preserving human oversight for more nuanced aspects of care.
Swara Honagudi· Technoarete Transactions on...· 0 citations
This study examines the influence of emotional and artificial intelligence in Tanzania’s public sector in the era defined by rapid digital transformation and increasing complexity in service delivery, the synergy between human centered skills and technological innovation has become important. This research adopted a qualitative case study approach focusing on two major public institutions, Tanzania Posts Corporation (TPC) and Tanzania Revenue Authority (TRA). Through the purposive sampling, insights were gathered from HR officers, heads of departments and Ict personnel involved in workforce development. The study's conclusions show. that emotional significantly enhances interpersonal communication, leadership, emotional regulations and adaptability, all of which are the key to high performing teams and effective public service conversely. Artificial intelligence improves efficiency, accuracy and streamlines. HR procedures like data management and hiring. Together, EI and AI contribute to creating a resilient, future-readily workforce capable of navigating the challenges of a dynamic public service landscape. The study comes to the conclusion that integrating EI and AI is not only advantageous but also essential for long-term workforce growth in Tanzania's public sector. It suggests investing in cutting-edge technologies, ongoing training, and legislative changes to promote innovation, learning, and efficient service delivery.
Juma H. Uledi· Journal of Leadership, Strat...· 0 citations
Results show that greater user autonomy and participatory linguistic styles significantly enhance engagement, whereas authoritative language reduces it, emphasizing the importance of designing DCs that empower users and create authentic connections.
Aitor Ezker‐Galech, Raquel Chocarro, Mónica Cortiñas et al.· Psychology & Marketing· 0 citations
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