Research on collaboration between human and non-human intelligent agents is extensive, yet a deeper understanding of the specific management and organizational challenges and the research methods used to study them is still needed. A systematic literature review was conducted following methodological guidelines to address this gap, with the PRISMA 2020 flow diagram used to document the process. This study explores two key research questions: (RQ1) What specific management and organizational challenges are investigated in human-AI collaboration? (RQ2) What research methods are commonly employed in this field? Data were retrieved from Scopus (486 documents) and Web of Science (385 documents), resulting in 95 studies in the final analysis. The review identifies five key categories of management and organizational challenges: (1) Hybrid human-AI teams, (2) AI integration in work processes, (3) Human-AI decision-making, (4) Trust in AI, and (5) Human-robot collaboration (HRC). Quantitative methods were more frequently used than qualitative approaches, with experimental studies—particularly simulation designs—being the most common. In qualitative research, grounded theory and case study designs were equally prominent. The findings contribute to the ongoing discourse on human-AI collaboration by mapping key challenges and methodological trends, providing insights for future research and organizational practice .