Contemporary Trends and Challenges in Hr Technologies
Abstract
The study synthesizes peer-reviewed evidence from 2024–2025 on HR technologies that restructure recruitment workflows in large U.S. organizations. Relevance follows from persistent hiring frictions—multi-week time-to-fill, high screening labor, and delayed ramp-up—which curb innovation in technology sectors. Novelty lies in an integrated reading that couples embedding-first retrieval and learning-to-rank with governance-by-design for candidate-facing modules. The review maps how résumé/job-description embeddings, compact foundation-model filters with post-hoc explanations, and skill-graph enrichment improve early-stage recall and shortlist quality, while chat-based and video-interview interfaces require validity safeguards. The paper formulates a design goal for integration-first platforms: overlay advanced scoring and explanations on incumbent ATS timelines rather than replace them. Methods include comparative reading of algorithmic evaluations (nDCG, RBO, F1/recall), legal-doctrinal synthesis on fairness and auditability, and triangulation with empirical studies of applicant behavior in automated interviews. Sources span ten recent articles in information systems, management, law, and psychology. The conclusion specifies implementation controls (feature governance, logging, escalation) and a measurement plan suitable for enterprise deployments in high-volume tech hiring.
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