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

2026-01-04

arXiv.org

AI Summary

This study investigates whether workers in emerging economies exposed to automation can realistically transition to safer occupations and identifies structural barriers to such mobility. Leveraging a knowledge graph encompassing nearly 10,000 Egyptian occupations, 20,000 skill activities, and over 80,000 occupation–skill relationships, the research quantifies the proportion of workers in high-automation-risk occupations who possess viable transition pathways—defined as sharing at least three skills with a target occupation and achieving a skill transferability rate of at least 50%. The analysis reveals that 20.9% of occupations face high automation risk, yet only 24.4% of affected workers have feasible transition paths. Among the 4,534 viable pathways identified, 15.6% involve process-oriented skills, underscoring their potential as a critical intervention lever. These findings highlight the necessity of proactively constructing occupational transition channels rather than relying on passive skill matching.

Technology Category

• Intelligent Robots: Other Foundations and Applications
• Machine Learning: Transfer, Domain Adaptation, Multi-Task Learning
• Planning, Routing, and Scheduling: Activity and Plan Recognition

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs

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.

Problem

• labor market transitions
• automation risk
• skill transfer
• structural mobility barrier
• job displacement

Innovation

• knowledge graph
• labor market transitions
• automation risk
• skill transferability
• structural mobility barrier