Graph-Based Analysis of AI-Driven Labor Market Transitions: Evidence from 10,000 Egyptian Jobs and Policy Implications

• URL: http://arxiv.org/abs/2601.06129v1
• Date: Sun, 04 Jan 2026 21:19:58 GMT
• Title: Graph-Based Analysis of AI-Driven Labor Market Transitions: Evidence from 10,000 Egyptian Jobs and Policy Implications
• Authors: Ahmed Dawoud, Sondos Samir, Mahmoud Mohamed,
• Abstract summary: While 20.9% of jobs face high automation risk, only 24.4% of at-risk workers have viable transition pathways.<n>Among 4,534 feasible transitions, process-oriented skills emerge as the highest-leverage intervention.
• Score: 1.9280643035418399
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: How many workers displaced by automation can realistically transition to safer jobs? We answer this using a validated knowledge graph of 9,978 Egyptian job postings, 19,766 skill activities, and 84,346 job-skill relationships (0.74% error rate). While 20.9% of jobs face high automation risk, we find that only 24.4% of at-risk workers have viable transition pathways--defined by $\geq$3 shared skills and $\geq$50% skill transfer. The remaining 75.6% face a structural mobility barrier requiring comprehensive reskilling, not incremental upskilling. Among 4,534 feasible transitions, process-oriented skills emerge as the highest-leverage intervention, appearing in 15.6% of pathways. These findings challenge optimistic narratives of seamless workforce adaptation and demonstrate that emerging economies require active pathway creation, not passive skill matching.

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