Artificial Intelligence Copilot and Monitoring Digital Traces: Guiding Agile Leaders Toward Ethical Work Governance

Abstract

This article presents a systematic literature review and a conceptual modeling framework designed to explore the intersection of artificial intelligence (AI), agile leadership, and ethical governance within modern organizations. Drawing on socio-technical systems (STS) theory, this study systematically examines how agile project management practices are reshaped by the combination of digital trace analysis and natural language processing (NLP) to assess team dynamics. Based on a rigorous selection of high-quality indexed articles, including recent computational datasets from EPJ journal, our synthesis reveals a growing structural tension between algorithmic performance optimization and human well-being. More specifically, qualitative and bibliometric analysis highlights three critical risks: algorithmic bias in task assignment, intrusive surveillance, and loss of trust within the team. To address these issues, this research conceptualizes a new ethical governance framework that implements digital incentives. In doing so, we demonstrate how to transform intrusive surveillance into a constructive resource, there by enhancing social sustainability, data integrity, and work ethics within agile teams.