Objective To evaluate the diagnostic efficacy of artificial intelligence-assisted cytology in detecting esophageal cancer and precancerous lesions. Methods Outpatients who were scheduled for endoscopic examination at the Second Affiliated Hospital of Baotou Medical College from June 21, 2021 to May 12, 2022 were selected. Artificial intelligence-assisted cytology and painless gastroscopy (add narrow-band imaging and biopsy pathology when need) (hereinafter referred to as gastroscopy) were performed. The detection rates of esophageal cancer and precancerous lesions by the two methods were compared. Taking gastroscopy as the standard, sensitivity, specificity, positive predictive value, negative predictive value of artificial intelligence-assisted cytology diagnosis were calculated to verify its diagnostic efficacy. Results A total of 849 patients meeting the inclusion criteria were included. Artificial intelligence-assisted cytology detected 365 cases of esophageal lesions, with a detection rate of 42.99%. One hundred cases of esophageal cancer, precancerous lesions, and atypical squamous cell hyperplasia were detected, with a detection rate of 11.78%. Gastroscopy detected 281 cases of esophageal lesions, with a detection rate of 33.10%. Eighty cases of esophageal cancer and precancerous lesion were detected, with a detection rate of 9.42%. The sensitivity and specificity of artificial intelligence-assisted cytology diagnosis were 81.25% (65/80) and 95.45% (734/769), respectively. The positive predictive value was 65.00% (65/100), and the negative predictive value was 98.00% (734/749). The area under the receiver operating characteristic curve of artificial intelligence‑assisted cytology in dectecting esophageal cancer and precancerous lesions was 0.785. Conclusion Artificial intelligence-assisted cytology demonstrates relatively high sensitivity and specificity in diagnosing esophageal cancer and precancerous lesions, exhibiting good diagnostic performance for esophageal lesions.