Artificial Intelligence Applications in Human Resource Management

Ćormarković, Teodora; Dražeta, Lazar

doi:10.15308/sinteza-2022-414-420

Cited by 1 publication

(2 citation statements)

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“…For example, if the objective is to reduce turnover costs, the key performance measures may include cost-per-hire, turnover rates and costs, time-to-fill, new-hire satisfaction with orientation, supervisor satisfaction with orientation (learning and growth) and others. The aforementioned traditional systems, where data mining algorithms were applied for data analysis, have been recently upgraded with modern ML algorithms that enable more advanced analytics with greater precision in providing proper knowledge to decision makers (Ćormarković & Dražeta, 2022). Therefore, this level of AI applications is mostly based on ML algorithms implementation.…”

Section: Second Level: Smart Analytics Systems For Decision Makersmentioning

confidence: 99%

“…Large-scale development of artificial intelligence (AI) applications, brought a new dimension to human resource management (HRM), where the traditional approach has gradually been overcome and moved towards an intelligent (cognitive) approach within HRM (Ćormarković & Dražeta, 2022). Existing processes are becoming more agile, and some new ones are also appearing (Edlich et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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The levels of artificial intelligence application in human resource systems

Ćormarković¹,

Dražeta²,

Njeguš³

2022

EurJ Appl Econ

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As human capital has become a vital asset in contemporary businesses, utilizing human resources exceeds HRM function towards strategic business partnership within organizations. The key enabling factor was global ICT development that changed functional roles and responsibilities within operating business models and introduced machine intelligence that increased organizational capabilities while reducing human involvement. The paper discusses the current state of AI applications in HRM systems. Emphasis is placed on clarifying technological features and goals, as well as the evolution of existing HRM systems. Furthermore, the paper provides the framework of AI application levels that serve as a foundation for understanding the current operational potential and provides useful evidence for the future development of HRM systems.

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Section: Second Level: Smart Analytics Systems For Decision Makersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%