Artificial intelligence adoption in extended HR ecosystems: enablers and barriers. An abductive case research

Abstract

Artificial intelligence (AI) has disrupted modern workplaces like never before and has induced digital workstyles. These technological advancements are generating significant interest among HR leaders to embrace AI in human resource management (HRM). Researchers and practitioners are keen to investigate the adoption of AI in HRM and the resultant human-machine collaboration. This study investigates HRM specific factors that enable and inhibit the adoption of AI in extended HR ecosystems and adopts a qualitative case research design with an abductive approach. It studies three well-known Indian companies at different stages of AI adoption in HR functions. This research investigates key enablers such as optimistic and collaborative employees, strong digital leadership, reliable HR data, specialized HR partners, and well-rounded AI ethics. The study also examines barriers to adoption: the inability to have a timely pulse check of employees' emotions, ineffective collaboration of HR employees with digital experts as well as external HR partners, and not embracing AI ethics. This study contributes to the theory by providing a model for AI adoption and proposes additions to the unified theory of acceptance and use of technology in the context of AI adoption in HR ecosystems. The study also contributes to the best-in-class industry HR practices and digital policy formulation to reimagine workplaces, promote harmonious human-AI collaboration, and make workplaces future-ready in the wake of massive digital disruptions.

Keywords: AI ethics; HR data; artificial intelligence; digital leadership; human-machine collaboration; optimistic; partners.

Figure 1

Boundary conditions of the research.

Figure 2

AI adoption levels.

Figure 3

Coding methodology.

Figure 4

Proposed theoretical model for AI adoption in HR ecosystems.

Figure 5

Proposed additions to the UTAUT framework.