Uppsats

The Role of AI In HR Digitalization in Enhancing Employee Engagement and Operational Efficiency

Master-uppsats

KTH/Skolan för industriell teknik och management (ITM)

Publicerad: 2025

Språk: Engelska

Sammanfattning

Technology is undergoing fast development, where new opportunities for organizations appear to embrace new methods that the new technologies support. One example of such technology is artificial intelligence (AI), which is currently being adopted within organizations to remain competitive. This alters the way organizations operate, including HR practices that are transitioning from traditional processes to more digitalized ones. Previous research has put a lot of focus on AI implementations effects on onboarding and recruiting, causing its effects on employees' everyday work to be understudied. To address this gap, this study aims to investigate AI’s impact on employee engagement and operational efficiency by focusing mainly on the perspectives of people having AI driven HR processes implemented into their everyday work. To do this, a single case study has been conducted to focus on an organization that has implemented AI in HR, where data has been collected through interviews and secondary data. The findings highlight both opportunities and challenges related to AI adoption in HR, where some of the findings are more dependent on context, while others are more reliant on the technology itself and are therefore more likely transferable to other organizations adopting AI in HR. The findings of this study indicatethat AI adoption introduces both supportive and hindering factors of employee engagement. However, the results indicate that AI predominantly acts as an amplifier of supportive factors and can in that way enhance engagement among employees. Literature has found that higher levels of engagement contributes to operational efficiency. This, combined with findings of this study which identified direct contributors to operational efficiency shows that AI adoption in HR contributes to enhanced operational efficiency.

Information

Författare
Erlandsson, Pim
Lärosäte / institution
KTH/Skolan för industriell teknik och management (ITM)
Publiceringsdatum
2025
Uppsatstyp
Master-uppsats
Språk
Engelska

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