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  4. Artificial Socialization? How Artificial Intelligence Applications Can Shape A New Era of Employee Onboarding Practices
 
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Artificial Socialization? How Artificial Intelligence Applications Can Shape A New Era of Employee Onboarding Practices

Journal
Hawaii International Conference on System Sciences (HICSS)
Type
conference paper
Date Issued
2023-01-06
Author(s)
Ritz, Eva  
Fabio, Donisi
Elshan, Edona  
Rietsche, Roman  
Research Team
IWI6, Micha Brugger, Damian Falk, Andreas Göldi, Alexander Meier, Eva Ritz
Abstract
Onboarding has always emphasized personal contact with new employees. Excellent onboarding can extend employee retention and improve loyalty. Even in a physical setting, the onboarding process is demanding for both the newcomer and the onboarding organization. Remote work, in contrast, has made this process even more challenging by forcing a rapid shift from offline to online onboarding practices. Organizations are adopting new technologies like artificial intelligence (AI) to support work processes, such as hiring processes or innovation facilitation, which could shape a new era of work practices. However, it has not been studied how AI applications can or should support onboarding. Therefore, our research conducts a literature review on current onboarding practices and uses expert interviews to evaluate AI's potential and pitfalls for each action. We contribute to the literature by presenting a holistic picture of onboarding practices and assessing potential application areas of AI in the onboarding process.
Language
English
Keywords
artificial intelligence
onboarding
employee
socialization
skill profile
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Business Innovation
Publisher place
Maui, Hawaii, USA
Event Title
Hawaii International Conference on System Sciences (HICSS)
Event Location
Maui, Hawaii, USA
Event Date
3-6 Jan 2023
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/107805
Subject(s)

information managemen...

Division(s)

IWI - Institute of In...

Eprints ID
267581
File(s)
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Thumbnail Image
Name

JML_919.pdf

Size

298.62 KB

Format

Adobe PDF

Checksum (MD5)

424e0e3e87f0680b61cd7103d9632b82

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