This study surveys ~300 Egyptian agrifood SMEs to build and validate an AI Readiness Index, identifying which firm, owner, and ecosystem factors explain differences in AI adoption readiness and where policy support should be targeted.

Focus area

Egypt's AI strategy targets large firms and public administration, leaving agrifood SMEs underexamined despite constraints like seasonality, thin margins, and fragmented supply chains. This project examines AI adoption readiness among Egyptian agrifood SMEs, combining survey data with statistical validation (factor analysis, clustering, regression) to build a diagnostic tool showing which readiness dimensions are most binding, and for which firms, so policy support can be targeted.

Key objectives

• Measure AI readiness across strategic, governance, data, ecosystem, human-capital, resilience, and value-chain dimensions in ~300 agrifood SMEs.
• Validate a composite AI Readiness Index via factor analysis and alternative weighting schemes.
• Segment firms into readiness clusters using k-means/hierarchical clustering.
• Identify firm and owner traits predicting readiness via ordinal logistic regression, informing targeted policy design