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<p>This study investigates the effect of artificial intelligence (AI) adoption on profitability metrics in Egyptian banks, examining financial stability as a moderating variable in this relationship. A regression model using panel data with fixed effects analysed 153 observations from 17 Egyptian banks (2016-2024). The AI ratio (technological assets/total assets) served as the independent variable, with Return on Assets (ROA), Return on Equity (ROE), Gross Profit Margin (GPM), Net Interest Margin (NIM), and AU as dependent profitability measures. The Z-score index measured financial stability as a moderate variable, while CAR, bank size, and age were control variables. AI positively affects ROE and NIM significantly. Conversely, it negatively affects GPM and Asset Utility (AU) due to high implementation costs. Furthermore, financial stability moderates the AI-profitability relationship, transforming AI’s negative effects on GPM and AU into positive ones while strengthening AI’s positive influence on ROA. This research fills a critical gap by developing an AI-integrated, context-sensitive framework specifically for Egyptian banks, extending beyond developed markets to provide empirical evidence and regulatory recommendations for emerging economies.</p>

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The Era of AI: Development of Artificial Intelligence (AI) and its Effect on Advancing Banks Profitability: The Role of Financial Stability as Moderating Variable in Egyptian Banks

  • 期刊论文

  • 发表日期：

    2026年4月16日

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  • Mona Ali Khalil,
  • Mohamed Abdelraouf

摘要

This study investigates the effect of artificial intelligence (AI) adoption on profitability metrics in Egyptian banks, examining financial stability as a moderating variable in this relationship. A regression model using panel data with fixed effects analysed 153 observations from 17 Egyptian banks (2016-2024). The AI ratio (technological assets/total assets) served as the independent variable, with Return on Assets (ROA), Return on Equity (ROE), Gross Profit Margin (GPM), Net Interest Margin (NIM), and AU as dependent profitability measures. The Z-score index measured financial stability as a moderate variable, while CAR, bank size, and age were control variables. AI positively affects ROE and NIM significantly. Conversely, it negatively affects GPM and Asset Utility (AU) due to high implementation costs. Furthermore, financial stability moderates the AI-profitability relationship, transforming AI’s negative effects on GPM and AU into positive ones while strengthening AI’s positive influence on ROA. This research fills a critical gap by developing an AI-integrated, context-sensitive framework specifically for Egyptian banks, extending beyond developed markets to provide empirical evidence and regulatory recommendations for emerging economies.