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Artificial intelligence (AI) is an essential technology of the 21st century (Buxmann & Schmidt, 2021; Jain et al., 2018). Both research and practice apply it to various domains, including automotive (Lorente et al., 2021) and finance (Goodell et al., 2021), or business divisions like human resource management (HRM) (Tambe et al., 2019). Modern information technology (IT) applications of AI include automated programming and interactive interpreters (Russell et al., 2016).
AI was first mentioned by McCarthy et al. (1955) nearly 70 years ago. However, AI prospers more than ever due to technological advancements (Rai et al., 2019). About 20 years ago, Kurzweil (2005) declared AI to be deeply integrated in all domains and business divisions. McLellan (2022) recently repeated the call for small- and medium-sized enterprises (SME) to focus on AI adoption. Through productivity-enhancing automation and job replacement, AI will change society by decreasing (Chelliah, 2017) or increasing (Daugherty et al., 2019) the number of employees.
HRM deals with human resources, which play a prominent role within a company. As such, human resources represent a significant success factor for an organization (Noe et al., 2020). Combining the potential of AI technology with the essential role of HRM is, therefore, highly relevant for SME.
Organizations face several challenges in implementing AI. They must ensure that organizational prerequisites (i.e., AI strategy, AI knowledge, and employee qualification) are covered while obeying principles of ethics and privacy (Dahm & Dregger, 2020; Vrontis et al., 2022). Applications of AI in subareas of HRM include strategic planning, personnel search and acquisition (Channabasamma et al., 2021; Dahm & Dregger, 2019; Knobloch & Hustedt, 2019; Pandey & Bahukhandi, 2022; Vrontis et al., 2022), personnel selection (Vrontis et al., 2022), administrative processing of HRM activities (Dahm & Dregger, 2019; Knobloch & Hustedt, 2019; Strohmeier & Piazza, 2015; Vrontis et al., 2022), communication with (potential) employees (Dahm & Dregger, 2019; Iyer et al., 2020; Knobloch & Hustedt, 2019), development and implementation of training measures (Knobloch & Hustedt, 2019), employee evaluations (Vrontis et al., 2022), development of measures for employee retention (Atef et al., 2022), and evaluation of the potential of managers (Dahm & Dregger, 2019). Big data and digital transformation challenge SME by changing established market and communications processes. Therefore, SME must reinvent their business models, as AI’s automated processes can lead to a growing demand for AI specialists (Neuburger et al., 2021).
As Tambe et al. (2019) note, AI faces four challenges when applied in HRM: (1) complex phenomena; (2) small data sets; (3) accountability questions; and (4) adverse employee reactions to AI-based management decisions. Zhu et al. (2021) highlight general employees’ perceptions of AI in the implementation process, including degrees of technology optimism toward AI. Companies should use several strategies to adapt to perceptions surrounding AI’s cognitive and operational capabilities (Zhu et al., 2021). Furthermore, there is research regarding the attitude toward AI (Sindermann et al., 2021; Schepman & Rodway, 2020; Fast & Horvitz, 2017), e.g., in recruiting (Pandey & Bahukhandi, 2022).