AI-Induced Labor Market Shifts in the U.S.: Occupational Exposure and Regional Disparities

AI-Induced Labor Market Shifts in the U.S.: Occupational Exposure and Regional Disparities | 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 Research Article AI-Induced Labor Market Shifts in the U.S.: Occupational Exposure and Regional Disparities Jiamei Wang, Dongyan Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7646097/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study explores how Artificial Intelligence (AI), particularly the rise of Large Language Models (LLMs), is unevenly transforming the U.S. labor market. Focusing on wage growth and employment patterns across various occupations and regions, we introduce two new indices—the Replacement Exposure Index (REI) and the Assistive Exposure Index (AEI)—to measure the susceptibility of jobs to automation or enhancement by AI. Using panel data from the U.S. Bureau of Labor Statistics and the O*NET Resource Center, we conduct a Difference-in-Differences (DID) analysis with the emergence of LLMs in 2022 as a key turning point. Our findings indicate that occupations exposed to AI experience both wage increases and shifts in employment structures, with more pronounced effects in high-tech states like California and Massachusetts. In contrast, low-tech states demonstrate more modest labor responses. These results reveal a pattern of wage polarization and regional inequality driven by exposure to AI. The study contributes to the growing body of research on technological change and labor markets by providing occupation- and region-specific evidence. Our results also underscore the pressing need for policy measures—particularly in education, workforce training, and regional innovation—to mitigate inequality and foster inclusive adaptation to AI-driven changes. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7646097","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":517576134,"identity":"589481b8-bd99-4b57-8cda-17b9198f2258","order_by":0,"name":"Jiamei Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBACxgYGhgMwjgFDBZBkZm4gRcsZkBZG/FrQDGiDGYMHMLefTjzwsc0uT96Bx6Do5rzaaP52oJYfFdtwm9uTu+HgzLbkYsMDPAbGuduO5844zNjA2HPmNh6/5G44zLuNOXFjA+8GoJZjuQ1ALcyMbXi09L/dcPjvtnqoljnHcucT1DIDaAvjtsOJ8xlAWhpqQFxCWt5uONj773jiBmb+D8Y5xw7kbgRqOYjPL4b9uZs//DhTnTi/vS3NOKemLnfe+cMHH/yowKOlAcowOMzAZsDAcBjMOYBTPRDIwxkNDMwPGBjq8CkeBaNgFIyCEQoAqIFk66Kaox8AAAAASUVORK5CYII=","orcid":"","institution":"Texas A\u0026M University","correspondingAuthor":true,"prefix":"","firstName":"Jiamei","middleName":"","lastName":"Wang","suffix":""},{"id":517576135,"identity":"76de5419-935b-4118-a402-10f54649c96b","order_by":1,"name":"Dongyan Wang","email":"","orcid":"","institution":"Texas A\u0026M University","correspondingAuthor":false,"prefix":"","firstName":"Dongyan","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-09-18 06:53:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7646097/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7646097/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91803005,"identity":"355f937f-5917-4e40-a25f-c2edb41ba998","added_by":"auto","created_at":"2025-09-22 00:43:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":926869,"visible":true,"origin":"","legend":"","description":"","filename":"AILABOURMARKET.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7646097/v1_covered_b0168a22-409f-4c3f-b1fa-dfd4f5cca776.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"AI-Induced Labor Market Shifts in the U.S.: Occupational Exposure and Regional Disparities","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7646097/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7646097/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study explores how Artificial Intelligence (AI), particularly the rise of Large Language Models (LLMs), is unevenly transforming the U.S. labor market. 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