Purpose This paper aims to examine the challenges of implementing artificial intelligence (AI)-powered performance management systems. It proposes principles for more human-centred approaches that balance efficiency with employee well-being and dignity. Design/methodology/approach Drawing on recent labour disputes in Australia and existing literature on AI integration and performance management, this conceptual paper analyses the tensions inherent in algorithmic performance monitoring. It develops a framework for reimagining performance management in the AI era. Findings The paper argues that surveillance-based, AI-driven performance management systems create significant tensions between productivity optimisation and worker well-being. Success requires moving beyond algorithmic control towards augmentation models that preserve human agency, incorporate contextual understanding and balance quantitative metrics with qualitative judgement. Practical implications The paper provides human resources leaders with principles and practical guidance for implementing AI-enhanced performance management systems that support both organisational objectives and employee dignity, trust and engagement. Originality/value This paper contributes to the emerging discourse on AI in Human Resource Management by critically examining the limitations of algorithmic control approaches and proposing alternative frameworks that prioritise human-centred design and balanced governance structures.
Tenakwah et al. (2026) studied this question.