The present paper, thus, investigates the link between AI-disclosure in annual reports and firm performance in the Egyptian financial industry. It explains how the number of appertained AI-words in the corporate disclosures would correspond to the different financial performance indicators to, inter alia, shed light on the effect that the implementation and reporting of AI has on the performance of the financial institutions. This study is a quantitative study that uses company-year data to conduct a simple linear regression analysis on 12 selected financial industry companies in EGX30 over the period of 2013-2023, giving a total of 132 firm-year observations. What this issue leads to is the fact that, in total, the relative frequency of all the terms associated with AI in the annual reports is captured by an independent variable called AIFREQ. Concerning dependent variables, it focuses on several financial performance indicators, including ROA, ROE, NIM, GPM, and OPM. The variables used in the model as control measures are firm size and capital adequacy ratio. The results revealed significant positive association of the frequency of AI-related disclosures with the financial performance measures used. Fixed frequency significantly explained 71.5% of variation in the NIM. Fixed The association with OPM was the smallest, but positive and significant. These findings give rise to the view that those firms that disclose more frequently in their annual reports on matters relating to AI also appear to be performing better financially across most performance metrics. This paper contributes to the literature by focusing on the Egyptian financial sector and investigating the effect of voluntary AI disclosures on financial performance, rather than the adoption of AI only. It provides new insights into the relation of the report of AI initiatives with various dimensions of financial performance in an emerging market setting.