Ethical Dimensions of Algorithmic Management: A Qualitative Systematic Review and Meta-Synthesis of AI-Based HR Practices, Employee Engagement and Performance Outcomes

Abstract

The rapid proliferation of Artificial Intelligence (AI) and algorithmic management practices has radically transformed traditional human resource functions, shifting workflows from human-centered leadership toward automated, data-driven governance. While extensive quantitative literature details the mechanical efficiencies of AI deployments on corporate output, a critical knowledge gap persists regarding the qualitative, human-centric paradox of these systems: how algorithmic surveillance and automated evaluations alter the psychological contract, create digital burnout and reshape employee engagement dynamics in the digital workplace. This qualitative systematic review and meta-synthesis directly addresses this gap by aggregating, appraising, and synthesising empirical qualitative evidence exploring how employees navigate the tension between technological optimisation and workplace alienation, and how these lived experiences ultimately govern human performance. A comprehensive search strategy will be executed across major international databases, including Scopus, Web of Science, CINAHL and Business Source Complete, to capture qualitative data. Methodological quality and study design rigor will be systematically evaluated using the Critical Appraisal Skills Programme (CASP) Qualitative Checklist and meta-aggregation will be utilised to extract and synthesise findings into robust thematic categories. Preliminary scoping indicates that the synthesis will illuminate critical themes regarding the erosion of worker autonomy, the psychological friction caused by "black-box" HR metrics and the vital role of algorithmic transparency in preserving workplace trust. Aligning with the conference’s mandate for ethical scholarship, this review advances organisational policy frameworks by establishing the human guardrails necessary to balance interdisciplinary innovation with workforce well-being.