AI-Augmented HRM: Transforming Talent Acquisition and Employee Experience in 2026

Abstract

Artificial Intelligence (AI) is becoming increasingly usual in HR management, especially in talent acquisition and AI-assisted decision making. But, in addition to the technological capacities, the successful application of AI needs HR professionals to understand and evaluate the recommendations of AI. In the present research, the impact of AI literacy and Explainable Artificial Intelligence (XAI) on AI-augmented talent acquisition is inves-tigated. Quantitative analysis was performed using 410 valid observations of HR managers interacting with AI recruitment systems under various conditions of XAI. Subjective perception of AI systems and objective understanding of AI recommendations in relation to Important Features, Counterfactuals and Model Criteria explanations were considered. It has been established that all three XAI methods increase subjective percep-tion significantly. Nevertheless, there is a huge difference in the way they affect objective understanding. Important Features greatly increase objective understanding, Counterfactuals do not matter at all and Model Criteria lead to a degradation of objective under-standing. It was found out that there is a positive relationship between AI literacy and objective understanding. The results of the research demonstrate that there should be balance between AI literacy, explanation design and human judgement for effective AI augmented HRM.