Human-AI collaboration in the workplace

Human-AI collaboration in the workplace refers to structured arrangements in which humans and artificial intelligence (AI) systems jointly perform work tasks (Sowa et al., 2021). In such arrangements, AI systems typically handle computationally intensive components of work, such as large-scale data processing, prediction, pattern recognition, and routine decisionmaking, while humans contribute contextual understanding, ethical judgment, creativity, and social intelligence (Alla, 2025). The central objective of this collaboration is augmentation rather than substitution: AI is designed to enhance human capability, reduce cognitive burden, improve productivity, and enable workers to focus on more strategic and meaningful tasks (Nguyen & Elbanna, 2025). This conceptualization positions human-AI collaboration not as a binary replacement model but as a dynamic and evolving partnership. It recognizes that human intelligence and machine intelligence each have distinct comparative advantages and that the optimal configuration involves complementary task allocation rather than wholesale automation (Bankins et al., 2023). A multilevel review of AI in organizations demonstrates that human-AI collaboration now spans diverse industries and hierarchical levels with the impact of AI extends beyond operational efficiency, encompassing employee experiences, team dynamics, and organizational structures (Bankins et al., 2023). At the individual level, AI influences autonomy, learning opportunities, and stress levels (Nguyen & Elbanna, 2025). At the team level, it reshapes coordination patterns and communication flows (Schmutz et al., 2024). At the organizational level, it affects performance metrics, structural design, and strategic decisionmaking capabilities (Przegalinska et al., 2025).