Government AI Readiness Index 2025: Egypt’s Position and Competitiveness Priorities

Executive summary

Oxford Insights’ Government AI Readiness Index 2025 places Egypt at rank 52 with a total score of 59.10. The result assesses how prepared government is to use artificial intelligence for public benefit; it is not a measure of AI adoption alone or a forecast of economic returns.

This edition introduces a major six-pillar redesign with 69 indicators. Egypt’s score of 59.10 and rank of 52 are valid for the 2025 methodology, but the apparent movement from earlier editions must not be presented as a like-for-like trend. The policy value lies in the pillar profile: it helps distinguish formal policy capacity from infrastructure, governance, public-sector adoption, innovation diffusion and resilience.

Edition and methodology

Composite scores combine multiple indicators and source years. A higher score or better rank should therefore trigger diagnostic investigation, not a stand-alone claim of causal improvement. Country coverage also changes across editions.

Egypt’s official pillar profile

ENCC reading: the profile should be used to identify the weakest links between strategy, enabling infrastructure, public-sector execution and the domestic technology ecosystem. Strong policy architecture creates value only when institutions can implement, procure, govern and scale responsible AI applications.

Why government AI readiness matters for competitiveness

• Capable public institutions can lower transaction costs, improve service quality and strengthen regulatory predictability.
• Reliable data and digital infrastructure support productivity, innovation and the scaling of technology-intensive firms.
• Responsible governance can increase trust and reduce legal, ethical, cybersecurity and exclusion risks.
• Public procurement and adoption can create demand for domestic solutions when competition, interoperability and accountability are protected.

ENCC policy priorities

1. Translate strategy into funded delivery portfolios: assign owners, milestones, budgets and measurable public-value outcomes to priority AI use cases.
2. Strengthen interoperable public data foundations: improve data quality, exchange standards, access controls and auditability across institutions.
3. Build responsible-AI assurance: establish risk classification, impact assessment, human oversight, procurement safeguards and incident reporting.
4. Expand implementation skills: develop multidisciplinary teams combining policy, service design, data, engineering, cybersecurity, legal and evaluation capabilities.
5. Use procurement to support diffusion: create transparent pathways for pilots and scale-up while preserving competition and avoiding vendor lock-in.
6. Measure outcomes beyond the index: track service time, cost, accessibility, error rates, user trust and productivity for deployed systems.

Monitoring indicators

• Edition-native Egypt rank, total score and pillar scores with methodology label.
• Share of priority AI projects with approved impact assessments and named accountable owners.
• Percentage of high-value datasets meeting quality, interoperability and access-control standards.
• Time from pilot approval to evaluated deployment and proportion of pilots that scale responsibly.
• Measured public-service outcomes and independent assurance findings.

Data and interpretation limits

The index is composite and depends on source availability, normalization, weighting and annual methodological decisions. Rank changes can reflect movements by other countries as well as Egypt’s own score. The 2025 redesign creates a clear break from the 2020–2024 framework; cross-break comparisons require an explicit reconciliation method and should not be described as mechanically continuous.

Official sources

• Official series page
• Official report
• Official data
• Official methodology report