Abstract The rapid expansion of data-driven Human Resource Management (HRM) and the integration of Artificial Intelligence (AI) into workforce processes have reshaped how organisations make decisions about recruitment, performance management, employee engagement, and workforce planning. While these tools offer significant advantages in terms of efficiency, accuracy, and predictive capability, they have simultaneously raised complex ethical concerns relating to privacy, transparency, consent, algorithmic bias, and the erosion of employee trust. As organisations collect increasing amounts of sensitive employee data—from biometrics and productivity analytics to behavioural insights—the risk of misuse or unintended harm becomes substantial. Building and maintaining trust therefore becomes a strategic imperative. This paper examines the ethical dimensions of HR data and AI usage, with a specific focus on how organisations operating in the digital era can balance innovation with responsible governance. The study synthesises insights from existing literature, identifies the gaps in ethical practices, and investigates how transparent communication, strong data governance frameworks, fairness auditing of AI systems, and participatory decision-making can support sustainable trust. Using a descriptive research design and a survey-based approach, this study analyses employee perceptions of ethical HR data practices across selected emerging-market organisations. Findings indicate that while employees recognise the efficiency benefits of AI-enabled HR practices, trust declines when data is collected without clarity on purpose or when algorithmic decisions appear opaque or biased. The paper concludes with practical recommendations for HR leaders, including the need for ethics-by-design frameworks, implementation of explainable AI, employee participation in data-related decisions, and rigorous compliance with data protection standards. By adopting responsible data practices, organisations can mitigate risks and strengthen long-term employee trust in the age of analytics and automation.
B et al. (Wed,) studied this question.