Therefore, the present study was conducted with the aim of artificial intelligence and the emergence of distinct job ecosystems in knowledge-based companies. This study is classified as exploratory research in terms of its applied purpose and the data collection method and was conducted in two qualitative and quantitative sections. The statistical population of the study in the qualitative and quantitative sections is university professors and managers of knowledge-based companies, of whom 20 were selected as sample members using purposive sampling, based on the principle of theoretical saturation. The data collection tool in the qualitative section is an interview and in the quantitative section, it is a questionnaire. In this study, in order to analyze the data in the qualitative part, the content analysis approach and coding method through MaxQDA software were used. And in the quantitative part, the fuzzy cognitive map method was used. The research findings showed that among the 20 identified outcomes, the formation of hybrid teams including humans and intelligent systems to achieve common goals with the central index (21/25), the necessity of continuous retraining and upgrading of skills (Reskilling & Upskilling) with the central index (03/25), and the collaborative coexistence between employees and intelligent systems in line with organizational goals with the central index (25) are, respectively, the most important outcomes of artificial intelligence in the formation of a distinctive job ecosystem in knowledge-based companies.