| Abstract [eng] |
The master's thesis investigates the factors influencing the adoption of Generative Artificial Intelligence (GDI) among knowledge workers. GDI, a subset of AI employing machine learning algorithms, generates diverse content like text, images, and audio based on input data. The study emphasizes GDI's transformative potential in revolutionizing businesses by enhancing productivity, automating tasks, and improving customer interactions. The research specifically focuses on knowledge workers, who play a crucial role in organizational growth and innovation due to their intellectual capabilities and problem-solving skills. The thesis explores the symbiotic relationship between AI and employees, underlining the importance of collaborative intelligence (CI) for the successful implementation of AI tools. CI, the fusion of AI and human intellect, is essential for maximizing the benefits of AI tools. However, challenges such as employee distrust, lack of understanding, and fear of job displacement can hinder the development of CI. The study also addresses the concept of trust in AI, emphasizing that employee trust is a critical factor in the acceptance and adoption of AI systems. Knowledge sharing and AI literacy are identified as key factors in fostering trust and facilitating the integration of AI into organizations. By providing employees with knowledge about AI's capabilities, limitations, and ethical considerations, organizations can alleviate concerns and promote a more positive perception of AI. The thesis provides a comprehensive overview of knowledge workers and their competencies. Knowledge workers are characterized by their intellectual abilities, problem-solving skills, and knowledge application in complex tasks. The study identifies essential competencies for knowledge workers, including technical skills, information literacy, communication, collaboration, critical thinking, creativity, and problem-solving. These competencies are crucial for knowledge workers to thrive in the evolving landscape of modern organizations, where technological advancements and the increasing complexity of tasks demand a diverse skill set. The research also delves into the adoption process of AI as a technological innovation within organizations. It highlights that the successful adoption of AI hinges on organizational readiness, employee attitudes, and the perceived benefits of AI. The study identifies factors influencing AI adoption, such as compatibility with existing systems, the relative advantage over traditional methods, and the complexity of implementation. It also discusses established models like the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), which are commonly used to assess technology adoption. However, the thesis acknowledges the limitations of these models in predicting the adoption of AI due to its intelligent nature, which sets it apart from conventional technologies. |
