This paper attempts to explore the effects of Artificial Intelligence (AI) application on banking soundness indicators using data of 119 countries during the period from 2020 to 2023, where AI application is measured by the scores of its dimensions and pillars. Besides, banking soundness has been measured mainly by CAMELS approach. Artificial Intelligence has been measured by three pillars: Government, Technology Sector, and Data and Infrastructure, where Government pillar includes 4 dimensions: Vision, Governance and Ethics, Digital Capacity and Adaptability. Besides, Technology Sector pillar includes 3 dimensions: Maturity, Innovation Capacity and Human Capital. In addition, Data and Infrastructure pillar includes 3 dimensions: Infrastructure, Data Availability and Data Representativeness. Using panel analysis according to GMM technique, results indicate that AI seems to have significant effect on asset quality, earnings and liquidity, without any evidence about its effect on capital adequacy. When investigating the effects of AI pillars on banking soundness indicators, capital adequacy seems to be affected by Government, Technology Sector, while asset quality seems to be affected by Data and Infrastructure. In addition, earnings and liquidity have been affected by Technology Sector. This means that all of the three AI pillars may affect banking soundness indicators. This is why, for each of the three hypotheses, the null hypothesis may be rejected and the alternative one may be accepted.