PACIS 2022 Proceedings


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New technologies and artificial intelligence (AI) are influencing the way the work is performed now and will be performed in the future. The World Economic Forum (2020) estimated that by 2025, machines will replace 85 million jobs. However, millions of new jobs facilitated by the collaboration of humans and machines will also emerge. Thus, it is important to understand the drivers of these changes to equip organizations and people with necessary knowledge and get ready for new opportunities. One of the prominent manifestations of AI in the workplace is the virtual assistant, a technology that is based on natural language processing and machine learning. Virtual assistants can be activated either via text or voice and are designed to automate certain tasks and improve employee productivity. Gartner predicted that by 2025, 50% of knowledge workers will use a virtual assistant daily (Bradley 2020). To achieve optimal workforce transformation, both organizations and employees should embrace AI. However, an interesting question is whether the employees are willing to accept AI, and if so, are there differences in individual acceptance? We propose that in addition to task characteristics, the AI acceptance is contingent upon individual user characteristics, such as personality traits. Personality is a combination of the attributes, qualities and characteristics of individuals that distinguish their behavior, thoughts, and feelings (Saucier and Srivastava 2015). Personality accelerates various aspects of human behavior including work, such as career mobility and career success, leadership, job satisfaction, and product preferences. Our aim in this research is to investigate the acceptance of AI-driven virtual assistants through the lens of individual employee characteristics. The results of this research will be useful to organizations that consequently can offer customized AI solutions to improve employee experience by adapting the communication behavior of virtual assistants to individual personality characteristics. In addition, the results will be useful to employees. By designing a virtual assistant that is compatible with an employee, we expect a better collaboration between humans and machines and consequently improved productivity and satisfaction. The study will be conducted in two stages. In the first stage, we will collect information about AI task characteristics through direct semi-structured interviews contrasted with the O*NET OnLine database sponsored by the U.S. Department of Labor (, as well as deployment of user personality characteristics. In the second stage, we will test potential AI solutions.



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