Veröffentlichungen von Laura Bayor

Acquiring skilled employees is among the top five most important IT management issues. Artificial intelligence (AI) has the potential to transform talent acquisition (TA) and lead to a better future of work. However, not all of the possible futures are probable or preferable. Based on a Delphi study with C-level executives who are TA experts, we identify and evaluate AI opportunities and AI challenges, and recommend immediate and future actions organizations can take for integrating AI into TA.

Powered by generative artificial intelligence (AI), AI companions are designed to establish long-term relationships and friendships with human users, enabling human–AI social-oriented communication. However, this raises questions about the underlying reasons and contexts in which such communication occurs. While social exchange theory explains social-oriented communication between humans in terms of the exchange of benefits and costs, these exchanges may be different when dealing with a non-human entity such as an AI companion. Using a qualitative approach with semi-structured interviews, the benefits and costs of human–AI social-oriented communication and contextual patterns are identified. The results show that there are unique benefits and costs, that some assumptions of social exchange theory are challenged, and that there are distinct contextual patterns. By contextualizing social exchange theory, the findings contribute to AI companion and human–AI communication literature, and also have practical implications, particularly marketing implications for companies that want to offer AI companion services.