AI-driven talent management and organizational psychology: A structural model of talent pool effectiveness

This cross-sectional study examines associations among HR technology adoption (HRTA), an AI-supportive organizational psychological climate (OPF), employees' AI-driven psychological adoption (AIPA), and perceived talent pool management effectiveness (TPME). The archived analysis used covariance-based structural equation modeling with 184 respondents. To address conceptual ambiguity in the prior version, AIPA is defined consistently as employees' psychological acceptance of AI-enabled HR systems, reflected in trust, perceived fairness, and willingness to use such systems; OPF is treated as a provisionally reflective organizational-climate construct rather than as a collection of separate psychological theories. The available output shows positive unstandardized paths from HRTA to AIPA (B = 0.426, SE = 0.030, CR = 14.113, p < .001), from OPF to AIPA (B =0.567, SE = 0.020, CR = 28.215, p < .001), and from AIPA to TPME (B = 2.504, SE = 0.347, CR = 7.211, p < .001). Conditional direct paths from HRTA and OPF to TPME were negative (B = 0.570 and 0.849, respectively). Because the supplied analysis does not report global model-fit statistics, standardized effects, a validated four-factor measurement model, or bootstrapped indirect effects, the revised manuscript does not claim that the SEM is well fitting or that mediation has been established. The findings are therefore interpreted as cross- sectional associations that require confirmatory reanalysis before publication.