Scaling human-centered feedback: AI tools in continuous performance management

Purpose This study aims to examine how artificial intelligence (AI) is reshaping continuous performance management by scaling developmental feedback in hybrid and digitally connected workplaces. It explores the opportunities and ethical tensions that arise when AI-generated insights are integrated into performance feedback systems. Design/methodology/approach Drawing on recent HR technology trends and published research, this study synthesizes insights from organizational use cases and recent literature to evaluate the practical and relational impact of AI-powered feedback tools. Particular attention is paid to the role of chatbots, explainability and the importance of human oversight. Findings AI feedback systems offer value by identifying engagement patterns, supporting time-pressed managers and surfacing real-time coaching prompts. However, risks of dehumanization, misinterpretation and opacity persist. Ethical design, transparency and integration into existing relational practices are essential to ensure trust and effectiveness. Practical implications HR leaders should implement AI feedback tools gradually and with intentional guardrails. Emphasizing human interpretation, manager training and employee understanding of how AI functions are critical to fostering psychological safety and actionable feedback. Originality/value This study contributes a strategic and human-centered perspective on AI in performance management, blending technical insight with practical guidance. It frames AI as a tool for relational amplification rather than automation, offering HR practitioners a roadmap for ethical and effective adoption.