This study evaluates the accuracy of artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas. The review includes 25 peer-reviewed articles published from 2017 to July 2023, focusing on formulas such as Kane, PEARL DGS, Hill-RBF, Ladas, and others. The mean absolute error (MAE) and the percentage of patients within ±0.5 D and ±1.0 D were used to assess the accuracy. The results show that the Kane formula consistently achieved the lowest MAE and the highest percentage of patients within ±0.5 D, followed by the PEARL DGS formula. The Hill-RBF, Ladas, and Karmona formulas also performed well, but with some limitations. The study concludes that AI-based IOL power calculation formulas show promising results and have the potential to improve the accuracy of postoperative refractions after cataract surgery. However, further research is needed to validate these formulas, especially in different patient populations and with larger sample sizes.This study evaluates the accuracy of artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas. The review includes 25 peer-reviewed articles published from 2017 to July 2023, focusing on formulas such as Kane, PEARL DGS, Hill-RBF, Ladas, and others. The mean absolute error (MAE) and the percentage of patients within ±0.5 D and ±1.0 D were used to assess the accuracy. The results show that the Kane formula consistently achieved the lowest MAE and the highest percentage of patients within ±0.5 D, followed by the PEARL DGS formula. The Hill-RBF, Ladas, and Karmona formulas also performed well, but with some limitations. The study concludes that AI-based IOL power calculation formulas show promising results and have the potential to improve the accuracy of postoperative refractions after cataract surgery. However, further research is needed to validate these formulas, especially in different patient populations and with larger sample sizes.