Objective To explore the application of artificial intelligence (AI) in the examination of lumbar puncture for postgraduate students in neurology. Methods The lumbar puncture scores were further classified into speech, scene monitoring and motion evaluation, and they would be learned by the machine. Based on previous research, audio algorithm module, monitoring algorithm module and motion evaluation algorithm module are established. AI scores of lumbar puncture examination were compared with examiners' scores for 79 postgraduate students in neurology. Results AI scores were significantly lower than examiners' scores in speech score (52.86±3.25 points vs. 54.32±2.65 points, P＜0.05), while there was no significant difference between AI and examiners' scores in scene monitoring and motion evaluation (11.24±0.55 points vs. 11.15±0.62 points, P＞0.05; 28.09±11.37 points vs. 28.34±1.21 points, P＞0.05). Conclusion The application of AI technology in the evaluation of lumbar puncture operation of postgraduate students is objective and feasible, but the performance of the machine AI scoring system needs to be gradually iteratively optimized.