Artificial Intelligence and the Restructuring of Saudi Labor Markets: A Statistical Analysis of Job Displacement and Skill Transformation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Artificial Intelligence and the Restructuring of Saudi Labor Markets: A Statistical Analysis of Job Displacement and Skill Transformation Walaa Rezk This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6845043/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract This study investigates the impact of artificial intelligence (AI) on labor markets in Saudi Arabia, focusing on job displacement, skill transformation, and emerging forms of employment control. Drawing on publicly available data from the Ministry of Human Resources and Social Development, GASTAT, and the International Labour Organization (ILO), we employ a novel statistical framework combining longitudinal regression analysis, clustering techniques, and principal component analysis to assess the structural shifts in employment patterns across sectors between 2015 and 2024. The findings reveal a significant correlation between AI adoption and the reduction of routine-based jobs, particularly in administrative and clerical roles, while simultaneously increasing demand for high-skilled digital competencies. Furthermore, the research highlights how AI-driven automation reinforces labor segmentation by nationality, with foreign workers increasingly concentrated in vulnerable positions and nationals facing both exclusion and reconfiguration in the labor market. The paper contributes to critical debates on technological change and labor control by illustrating how AI reshapes not only work content but also worker subjectivity under techno-economic regimes. It challenges deterministic narratives of AI as purely disruptive, showing instead its dual role in both displacing and reconstituting labor within neoliberal development frameworks such as Vision 2030. Business and commerce/Business and management Business and commerce/Economics Business and commerce/Finance Social science/Economics Social science/Finance Social science/Science technology and society Social science/Social policy Artificial intelligence AI and labor market Automation Saudi Arabia Skill transformation Job displacement Vision 2030 Techno-economic control Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Sep, 2025 Reviews received at journal 07 Sep, 2025 Reviews received at journal 06 Sep, 2025 Reviews received at journal 02 Sep, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 27 Aug, 2025 Reviewers agreed at journal 26 Aug, 2025 Reviewers invited by journal 26 Aug, 2025 Editor assigned by journal 27 Jul, 2025 Editor invited by journal 22 Jul, 2025 Submission checks completed at journal 21 Jul, 2025 First submitted to journal 21 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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