20.500.12556/ReVIS-12231 AI‑Optimized, CX‑Driven: High‑Volume Hiring for Sales, Retention, Support and Operations Z AI optimizirano, na uporabniško izkušnjo usmerjeno: Množično zaposlovanje za prodajo, zadržanje strank, podporo in operacije 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. Namen:Namen prispevka je raziskati učinkovitost zaposlitvenega kanala, zasnovanega kot stroškovno učinkovit in usmerjen v izboljšanje uporabniške izkušnje (CX) s poudarkom na izkušnji kandidatov, da bi skrajšali čas zaposlovanja (TTH), povečali zadovoljstvo kandidatov ter dolgoročno izboljšali prvoletno zadržanje zaposlenih v podpornih funkcijah prodaje, podpore in operacij v podjetjih z množičnim zaposlovanjem. Oblika študije/metodologija/pristop: Uporabljen je bil mešani raziskovalni pristop, ki je črpal iz zapisov ATS in CRM, industrijskih standardov ter simulacij umetne inteligence. Kvantitativni podatki so temeljili na kvazi-eksperimentalnem dizajnu pred in po implementaciji, kvalitativni podatki pa na obdelavi naravnega jezika (NLP) izmenjav med kadroviki in kandidati z uporabo umetne inteligence ter na anonimnih anketah kandidatov. Kontrole z vključitvijo človeka (human-in-the-loop) in preverjanje pristranskosti so zagotavljali fleksibilnost pri uvajanju umetne inteligence. Ugotovitve: Uvedba umetne inteligence je prinesla pomembne operativne in izkustvene izboljšave. TTH se je zmanjšal z 28,4 na 14,7 dni (−48,2 %), zadovoljstvo kandidatov se je povečalo za 40 % (s 6,2 na 8,7), prvoletno zadržanje pa za 19 % (z 72,5 % na 86,3 %). Kvalitativni podatki so potrdili operativne učinkovitosti, večjo personalizacijo in občutek pravičnosti.Omejitve raziskave:Študija je bila omejena na eno veliko storitveno podjetje in temelji na pre–post dizajnu brez naključne kontrolne skupine, zato rezultatov ni mogoče posploševati. Prihodnje raziskave bi morale preučiti zaposlovanje, ki ga spodbuja umetna inteligenca in je podprto s CX, v bolj raznolikih organizacijskih kontekstih ter z longitudinalnimi ali kontroliranimi eksperimentalnimi načrti. Izvirnost/vrednost: Ob ustreznem upravljanju umetne inteligence (npr. revizije pristranskosti, nadzorni mehanizmi in transparentnost) lahko organizacije z množičnim zaposlovanjem skrajšajo čas zaposlovanja, izboljšajo zadržanje zaposlenih in znižajo stroške z uporabo pristopaAI-CX.Študija dokazuje, kako lahko umetna inteligenca hkrati izboljša učinkovitost in izkušnjo kandidatov. Artificial Intelligence Customer Experience High Volume Hiring Talent Acquisition First Year Retention Human in the Loop true false true Angleški jezik Slovenski jezik Članek v reviji 2025-09-19 12:39:22 2025-09-19 12:39:22 2025-10-01 14:19:06 0000-00-00 00:00:00 0 0 0 no. 2 Vol. 14 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 2025-09-11 2232-5107 2232-5697 https://doi.org/10.53615/10.53615/2232-5697.14.369-386 https://toknowpress.net/submission/index.php/ijmkl/article/download/225/148 1 e837a5cd-9544-11f0-9bb7-001a4af901a5 https://revis.openscience.si/Dokument.php?lang=slv&id=14277 https://toknowpress.net/submission/index.php/ijmkl/article/download/225/148 1 e8581bc7-9544-11f0-9bb7-001a4af901a5 https://revis.openscience.si/Dokument.php?lang=slv&id=14278 RAZ_Rodriguez_Guedes_Oriana_Valentina_0.pdf RAZ_Rodriguez_Guedes_Oriana_Valentina_0.pdf 1 DBBE7486B5BDC625040E839186C283A4 a4f44798455f8ebddd8215651efeb6719fbbbbbd081ecb337e3810e99b2681af 1dec917b-9545-11f0-9bb7-001a4af901a5 https://revis.openscience.si/Dokument.php?lang=slv&id=14279 Mednarodna fakulteta za družbene in poslovne študije 0 0 0