| Title: | AI‑Optimized, CX‑Driven: High‑Volume Hiring for Sales, Retention, Support and Operations |
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| Authors: | ID Rodriguez Guedes, Oriana Valentina (Author) |
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| Files: |  https://toknowpress.net/submission/index.php/ijmkl/article/download/225/148
https://toknowpress.net/submission/index.php/ijmkl/article/download/225/148
 RAZ_Rodriguez_Guedes_Oriana_Valentina_0.pdf (835,48 KB)
MD5: DBBE7486B5BDC625040E839186C283A4
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | MFDPŠ - International School for Social and Business Studies
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| Abstract: | Purpose: The purpose of this paper is to investigate the effectiveness of a hiring pipeline designed to be cost effective and improve customer experience (CX)—with an emphasis on candidate experience—to increase time to hire, candidate satisfaction, and eventual first year retention across supporting functions in sales, support, and operations in high-volume hiring firms.
Design/methodology/approach: A mixed-methods design was utilized and was derived from ATS, CRM logs, industry standards, and AI simulations. Quantitative information was based on a before-and-after quasi-experimental design. In contrast, qualitative information was based on natural language processing (NLP) of recruiter-candidate exchanges using total AI and anonymized candidate surveys. Human-in-the-loop controls and bias checks (metrics) assured flexibility in AI deployment.
Findings: Implementation of AI resulted in significant operational and experiential gains. Time to hire decreased from 28.4 to 14.7 days (−48.2%), candidate satisfaction was increased by 40% (6.2 to 8.7), and first-year retention was increased by 19% (72.5% to 86.3%). Qualitative data confirmed operational efficiencies, personalization, and increased perceived fairness.
Research limitations/implications: The study was limited to a single large service-focused company, which is based on a pre–post design, without a randomized control group design, and therefore, the findings are not generalizable. Future research should examine AI-driven CX-enhanced hiring in more diverse organizational contexts and longitudinal or controlled experimental designs.
Practical implications: With proper AI governance (e.g., bias audits, oversight checkpoints, and transparency), large volume hiring organizations can reduce hiring cycle time; improve retention; and reduce cost via AI-CX.
Originality/value: This study demonstrates how AI can jointly improve efficiency and the candidate experience and identifies governance practices needed for ethical and sustainable adoption at scale. |
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| Keywords: | Artificial Intelligence, Customer Experience, High Volume Hiring, Talent Acquisition, First Year Retention, Human in the Loop |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 11.09.2025 |
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| Numbering: | Vol. 14, no. 2 |
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| PID: | 20.500.12556/ReVIS-12231  |
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| ISSN: | 2232-5107 |
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| eISSN: | 2232-5697 |
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| DOI: | https://doi.org/10.53615/10.53615/2232-5697.14.369-386 |
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| Publication date in ReVIS: | 19.09.2025 |
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| Views: | 178 |
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| Downloads: | 6 |
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