Applications of artificial intelligence (AI) to material design have attracted increasingattention in recent years. Although AI-aided material design holds great promise forsome applications, whether it has surpassed human creativity remains uncertain. Theaim of the current study was to compare the divergent exploration capacity of AI withthat of humans on a material design task. Human participants were asked to find ahigh-performance lubricant molecule under searching conditions comparable to a state-of-the-art AI system. Results indicated that, on average, AI was able to find significantlybetter lubricant molecules. However, the best molecule found by AI fell short of the bestmolecule found by a human participant. Furthermore, the structural characteristics ofthe molecules found by AI and human participants differed significantly. These findings suggest that a state-of-the-art AI system is capable of surpassing human divergentexploration capacity in material design, as in other fields in which AI has advanced.Nevertheless, our results also demonstrate that human intelligence and AI can playcomplementary roles. This investigation opens up new possibilities for collaborative systems involving both AI and humans in material design.