<![CDATA[This study examines the causal relationships between artificial intelligence implementation, digital data sourcing practices, and candidates' perceptions of organizational attractiveness within the contemporary talent acquisition landscape. Adopting a rigorous empirical research design, a scenario based vignette survey experiment was conducted with a sample of 413 final year undergraduate university students in major Indonesian metropolitan areas. The econometric analyses, executed using paired Student's t-tests, reveal that increasing automation levels enhances corporate innovation signals but severely reduces perceived social environment viability and applicant intentions to apply. Furthermore, the utilization of personal online digital data significantly damages procedural fairness evaluations compared to professional tracking frameworks. Individual technology trust serves as a critical moderating variable, determining the magnitude of intention shifts among prospective business and engineering applicants. These findings suggest that organizations must strategically balance automated processing efficiency with candidate privacy boundaries to protect employer brand value. Navigating this sociotechnical dynamic allows recruiting organizations to leverage predictive talent analytics while maintaining high organizational attractiveness for top tier talent. ]]>
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