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Hiring Tomorrow's Talents : How Generative Artificial Intelligence Transforms Human Resources Recruitment

Title data

Banh, Leonardo ; Rex, Alexander ; Strobel, Gero ; Urbach, Nils:
Hiring Tomorrow's Talents : How Generative Artificial Intelligence Transforms Human Resources Recruitment.
In: 59th Hawaii International Conference on System Sciences (HICCS). - Maui, USA , 2026 . - pp. 5482-5491

Official URL: Volltext

Project information

Project financing: Fraunhofer Blockchain Center

Abstract in another language

The global talent shortage has become a universal challenge, prompting practitioners and researchers to explore digital innovations as potential solutions for acquiring the right talents. However, the role of emerging technologies like generative artificial intelligence (AI) in human resources (HR) remains largely uncharted territory. This article investigates generative AI’s transformative potential to augment recruiters’ daily operations. Through a qualitative interview study, we derive and illuminate the opportunities of generative AI within the recruitment domain, shedding light on its promising opportunities but also addressing inherent challenges. The findings of this study propose a theoretical model of generative AI in recruitment and how it empowers recruiters in their daily tasks to recruit tomorrow’s talents.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: AI, Organizing, and Management; Generative Artificial Intelligence; Grounded Theory; Human Resources; Recruitment
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Former Professors > Professor Information Systems Management and Strategic IT Management - Univ.-Prof. Dr. Nils Urbach
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Branch Business and Information Systems Engineering of Fraunhofer FIT
Research Institutions > Affiliated Institutes > FIM Research Center for Information Management
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 12 May 2026 06:34
Last Modified: 12 May 2026 06:34
URI: https://eref.uni-bayreuth.de/id/eprint/96924