ABSTRACT. The purpose of this study was to empirically examine the relationship between smart recruitment, predictive hiring algorithms, and the data-driven nature of artificial intelligence. Building my argument by drawing on data collected from the Boston Consulting Group, LinkedIn, MIT Sloan Management Review, and Statista, I performed analyses and made estimates regarding most useful interviewing innovations, adoption of specific artificial intelligence use cases (by category), levels of understanding for artificial intelligence-related technology and business context, and areas where artificial intelligence will impact recruiting. Empirical data for this study were gathered via an online survey conducted in the United States. The structural equation modeling technique was used to test the research model.
JEL codes: E24; J21; J54; J64

Keywords: automation; talent acquisition; smart recruitment; predictive hiring algorithm

How to cite: Bongard, Allan (2019). “Automating Talent Acquisition: Smart Recruitment, Predictive Hiring Algorithms, and the Data-driven Nature of Artificial Intelligence,” Psychosociological Issues in Human Resource Management 7(1): 36–41. doi:10.22381/PIHRM7120193

Received 8 January 2019 • Received in revised form 16 March 2019
Accepted 27 March 2019 • Available online 1 May 2019

Allan Bongard
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The Digital Dynamics Laboratory
at IISHSS, Ottawa, Canada

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