doctoral candidate
Russian Federation
student
student
UDC 004.08
The article presents a quantitative assessment of the investment attractiveness of deploying autonomous AI agents in recruitment processes. It justifies the shift from traditional automation to intelligent reengineering of hiring within the digital economy. Using cash flow simulation modeling, key financial metrics (NPV, ROI, DPP) are calculated across three implementation scenarios. The study demonstrates that employing agentic systems within a Human-in-the-Loop paradigm ensures rapid payback (under 1.3 years), even under conservative efficiency estimates. Key value drivers are identified, specifically the reduction of direct labor costs for routine operations and the minimization of foregone revenue from unfilled vacancies. Finally, recommendations for mitigating implementation risks, including data quality and algorithmic ethics, are proposed.
artificial intelligence, AI agents, recruitment, HR digital transformation, investment analysis, economic efficiency, NPV, ROI, hiring automation, Human-in-the-Loop, data economy
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