Labor Market Transformations in Egypt: Alternative Pathways for Jobs at Risk from Artificial Intelligence
The Egyptian Center for Economic Studies held a seminar on Sunday to present the results of the labor demand analysis in the Egyptian labor market for the fourth quarter of 2025, under the title “Labor Market Transformations: Alternative Pathways for Jobs at Risk from Artificial Intelligence”, sponsored by the National Bank of Egypt.
The seminar discussed, using quantitative evidence, the impact of artificial intelligence on job structures and the potential for transitioning to safer career pathways. It featured the latest findings of the quarterly labor demand analysis, alongside a key research presentation focusing on measuring job exposure to automation and identifying practical transition pathways for workers amid AI-driven transformations.
The results showed overall job growth during Q4 2025, with blue-collar jobs increasing by nearly 22% compared to the previous quarter, while white-collar jobs rose by 11%. However, job opportunities remained heavily concentrated in the Greater Cairo region, with weak representation across other governorates, reflecting the persistence of labor market centralization.
Flexible Work Patterns and Automation Risks
The analysis also highlighted a notable increase in demand for fresh graduates and the return of flexible work models—such as remote and hybrid work—for the first time in nearly a year. Job demand continued to concentrate in marketing, sales, services, and driving and delivery roles, while information technology, marketing, and advertising topped white-collar employment categories.
The AI-focused research revealed that out of 9,978 analyzed jobs in the Egyptian market, 2,082 jobs fall within the high-risk category for automation, accounting for 20.9% of total jobs—a figure closely aligned with global studies. The average automation risk across all jobs reached 38.5%.
The study relied on a “Knowledge Graph” methodology, building a model that includes 9,978 jobs and 84,346 skills, analyzing their interconnections based on skill similarity. This approach enabled the identification of “job communities” that allow more realistic career transitions without requiring a complete professional reset.
High-Risk Jobs and Transition Pathways
The analysis identified more than 1,063 transition pathways between high-risk jobs and safer alternatives, provided that skill overlap exceeds 50%, with an average overlap of 58.7%, indicating practical transition potential for a segment of the workforce.
However, only 509 of the 2,082 high-risk jobs—around 24.4%—were found to have clear transition pathways, while approximately 1,573 jobs (nearly 75%) lack sufficient alternatives, suggesting that a large portion of workers may face significant challenges without targeted training programs and supportive policies.
The research also identified a set of “bridging skills” that expand transition opportunities, including project planning and management, customer service and stakeholder management, leadership and team development, regulatory compliance, financial analysis, and inventory management. The study emphasized the importance of short, focused training packages centered on these skills to unlock hundreds of potential career pathways.
The findings concluded that artificial intelligence does not merely threaten jobs but necessitates the adoption of skill-based transition policies rather than traditional job classifications. Focusing on transferable skills, the study argued, can mitigate automation risks and generate new employment opportunities.
In this context, Adel Danesh emphasized that technological transformations throughout history have not only eliminated jobs but also created new ones, urging institutions to prepare through training and job redesign.