New technology-based recruitment methods
Oksanen, Reija (2018)
2018
Kauppatieteiden tutkinto-ohjelma - Degree Programme in Business Studies
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Hyväksymispäivämäärä
2018-05-21
Julkaisun pysyvä osoite on
http://urn.fi/URN:NBN:fi:uta-201805311872
http://urn.fi/URN:NBN:fi:uta-201805311872
Tiivistelmä
The transformation that recruitment might encounter due to big data analytics and artificial intelligence (AI) is particularly fascinating which is why this thesis focuses on the changes recruitment processes are and will be facing as new technological solutions are emerging. The aim and main objective of this study is to widen knowledge about new technology-based recruitment methods, focusing on how they are utilized by Finnish recruitment professionals and how the opportunities and risks that these new technological solutions provide in recruitment processes are experienced. Also, the future prospects of technology-based recruitment are examined.
The use of technology in recruiting practices is constantly becoming more and more routine amongst organizations. Recruiting as a whole has experienced a major change with new technologies providing quick, effective and cost-efficient ways of finding potential employees. Among these new technologies are big data and AI. Organizations have been collecting massive amounts of data, and now they are able to derive real value from big data and AI.
The research data was collected during the spring of 2018 by interviewing eight Finnish recruitment professionals who work among recruitment on a daily basis. Data was studied with qualitative methods by analyzing, coding and identifying themes.
As the aim of this thesis was to widen knowledge about the phenomenon of new technology-based recruitment methods the findings of this study appeared broad and diverse, highlighting the novelty of the phenomenon as opinions of the interviewees varied greatly. In Finland, AI is already utilized in recruitment at least to some extent. Three phases where AI can be of use during the recruitment process were identified: practical organizing, pre-screening applications and candidate communication.
The benefits and disadvantages of AI in recruitment aroused much discussion and opinions among the interviewees. Numerous opportunities and risks were identified when utilizing new technologies in recruiting. Among other things, accelerating the recruitment process, automation of routine tasks and increasing objectivity were seen as opportunities. The risk of discrimination, data distortion and invasion of privacy were considered as risks, among others.
The use of technology in recruiting practices is constantly becoming more and more routine amongst organizations. Recruiting as a whole has experienced a major change with new technologies providing quick, effective and cost-efficient ways of finding potential employees. Among these new technologies are big data and AI. Organizations have been collecting massive amounts of data, and now they are able to derive real value from big data and AI.
The research data was collected during the spring of 2018 by interviewing eight Finnish recruitment professionals who work among recruitment on a daily basis. Data was studied with qualitative methods by analyzing, coding and identifying themes.
As the aim of this thesis was to widen knowledge about the phenomenon of new technology-based recruitment methods the findings of this study appeared broad and diverse, highlighting the novelty of the phenomenon as opinions of the interviewees varied greatly. In Finland, AI is already utilized in recruitment at least to some extent. Three phases where AI can be of use during the recruitment process were identified: practical organizing, pre-screening applications and candidate communication.
The benefits and disadvantages of AI in recruitment aroused much discussion and opinions among the interviewees. Numerous opportunities and risks were identified when utilizing new technologies in recruiting. Among other things, accelerating the recruitment process, automation of routine tasks and increasing objectivity were seen as opportunities. The risk of discrimination, data distortion and invasion of privacy were considered as risks, among others.