Mohamed Galal, Head of AI and Data Management at National Bank of Egypt

As banks move AI from experimentation into production, fragmented tools, governance requirements and the challenge of bringing business and technical teams together can limit the ability to scale. Mohamed Galal,

Head of AI and Data Management at National Bank of Egypt, explains how the bank’ s adoption of Dataiku has created a unified foundation for AI development, strengthened governance and MLOps and opened the door to more advanced capabilities including AutoML, Generative

AI and agentic AI.

What were the biggest challenges you faced in maintaining legacy models, and how did the transition to a unified platform like Dataiku help address those issues?

One of the biggest challenges we faced with legacy environments was fragmentation. Models were developed across multiple tools and teams, leading to inconsistent governance, duplicated efforts and limited scalability. This made it difficult to maintain models efficiently, ensure compliance or adapt quickly to evolving business needs, particularly in a highly regulated banking environment.

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