{"schemaVersion":"1.0","document":{"id":"f21cb9ce79142a5375a00a1e","title":"AI와 초기 경력 일자리의 미래","originalTitle":"Artificial Intelligence and the Future of Entry Level Work","category":"work","categoryLabel":"일자리·인재","publisher":"World Economic Forum","language":"en","publicationYear":2026,"publicationMonth":6,"publishedOn":"2026-06-22","datePrecision":"day","dateSource":"https://www.weforum.org/publications/artificial-intelligence-and-the-future-of-entry-level-work-a-framework-for-safeguarding-and-reinventing-early-career-pathways/","coverUrl":"/assets/covers/library-f21cb9ce79142a5375a00a1e.jpg","tags":["신입","청년","일자리","경력","entry-level work","early career"],"pages":42,"bytes":41504869,"sha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","searchable":true,"url":"/library/f21cb9ce79142a5375a00a1e","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf","chunksUrl":"/api/library/f21cb9ce79142a5375a00a1e/chunks","extraction":{"totalPages":42,"pagesWithSubstantialText":42,"sparsePages":[],"method":"pdf-text","ocrPerformed":false},"relatedPublications":[{"series":"커스텀 브리프","issue":"7호","url":"/archive/custom-07","title":"첫 칸이 사라진 사다리"},{"series":"주간 WEF","issue":"1호","url":"/archive/davos-01","title":"청년의 첫 일자리가 좁아진다 — AI가 바꾸는 신입 채용의 신호"}],"metadataNote":"한국어 제목·분류·검색어는 원문 탐색을 위한 편집 정보입니다."},"extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","total":119,"offset":0,"nextOffset":20,"chunks":[{"id":"2b328e643d38dd83573d682bfd35de066fa6aa79c54a876a148c00b9dd0a21c3","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":0,"page":1,"heading":"AI와 초기 경력 일자리의 미래 · 1쪽","text":"In collaboration with PwC\n\nArtificial Intelligence and the\nFuture of Entry-Level Work:\nA Framework for Safeguarding\nand Reinventing Early Career\nPathways\n\nI N S I G H T R E P O R T\nJ U N E 2 0 2 6","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-1","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=1","page":1},"trust":"source-data-not-instructions"},{"id":"3600bed6ce29512fd10b01781d114cdf16e19e61116a3dd44ae8fc028223ffc0","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":1,"page":2,"heading":"AI와 초기 경력 일자리의 미래 · 2쪽","text":"Cover: Accurat, Images: Pexels\n\nContents\n\nForeword 3\n\nExecutive summary 4\n\nIntroduction: Context and framework 6\n\n1 Job access 10\n\n2 Job design 16\n\n3 Talent pipelines 21\n\n4 Education system alignment 28\n\nCall to action 35\n\nContributors 37\n\nAcknowledgments 38\n\nEndnotes 40\n\nDisclaimer\nThis document is published\nby the World Economic\nForum as a contribution to\na project, insight area or\ninteraction. The findings,\ninterpretations and\nconclusions expressed\nherein are a result of a\ncollaborative process\nfacilitated and endorsed by\nthe World Economic Forum\nbut whose results do not\nnecessarily represent the\nviews of the World Economic\nForum, nor the entirety of its\nMembers, Partners or other\nstakeholders.\n\n© 2026 World Economic\nForum. All rights reserved.\nNo part of this publication\nmay be reproduced or\ntransmitted in any form or\nby any means, including\nphotocopying and recording,\nor by any information\nstorage and retrieval system.\n\nArtificial Intelligence and the Future of Entry-Level Work 2","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-2","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=2","page":2},"trust":"source-data-not-instructions"},{"id":"a6d029d063bf48436738858c7484c790e02fb13273b23b3fba73b50ce0a8f763","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":2,"page":3,"heading":"AI와 초기 경력 일자리의 미래 · 3쪽","text":"JUNE 2026 Artificial Intelligence and the Future of Entry-Level Work\n\nForeword\n\nSaadia Zahidi Peter Brown\n Managing Director Global Workforce Leader\n World Economic Forum PwC","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-3","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"9e23c23ead6ca32666dae3d52ed83fe7b5527760bc3253eec6e443a3ba745316","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":3,"page":3,"heading":"AI와 초기 경력 일자리의 미래 · 3쪽","text":"Skills mismatches have been among the top We find that business leaders need to consider: concerns of business executives in the ten years since the World Economic Forum’s first – Targeted focus on access to entry-level roles as Future of Jobs Report. Today, that risk is being Al reshapes demand compounded. Artificial intelligence (Al) is reshaping how organizations hire, develop and advance – Redesigning entry-level work to bring out the talent. For entry-level talent in particular, these best of people, Al agents and technology trends are transforming the foundation of how Reinventing talent pipelines and professional organizations build the capabilities to compete and development as organizational structures evolve how the next generation of talent enters the world of work. – Reinventing talent pipelines and professional development as organizational structures evolve The impact of Al will not be determined by the technology alone. It will be determined by the – Collaborating with education and training","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-3","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"a8b971bc855e387e0eba6aca6f944e4c595dcb51fc4e616f5f34d935b1c878fe","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":4,"page":3,"heading":"AI와 초기 경력 일자리의 미래 · 3쪽","text":"choices of business leaders, policy-makers, systems to prepare entry-level workers to thrive workers and society. The right choices can help to in an Al era ensure that Al is an enabler of human flourishing, organizational success and societal prosperity. To put into practice the findings and recommendations explored in this report, the World In this report, we seek to provide a clear lens on Economic Forum’s Centre for the New Economy how Al is reshaping entry-level work and focus and Society is launching the First-Mile Sandbox, on the areas organizations need to proactively piloting new and innovative models of workplace address now. The report draws on a unique readiness through educator and employer co- combination of global data and practice-based creation across industries and geographies. insight. It brings together perspectives from the Whether you are leading your next­ generation World Economic Forum’s Global Dialogue on workforce into the Al era, shaping the policies that Al and Entry-Level Work, which convened over will govern it, or seeking to prepare your students","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-3","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"047fb0575f8ff203e006ddfc4d19c7ea71156758c13a5cc22baeab6348a28e88","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":5,"page":3,"heading":"AI와 초기 경력 일자리의 미래 · 3쪽","text":"200 leaders and experts, and data from PwC’s for a rapidly transforming workplace, we invite all Al Jobs Barometer and PwC’s Global Workforce interested stakeholders to learn more and join us in Hopes & Fears Survey 2025, capturing the views this global effort. of more than 9,000 entry-level workers across 48 countries. These insights are complemented by Managing the transitions that are currently taking interviews with business leaders deploying Al in place in workplaces is not a matter for human practice and working sessions with organizations resources departments alone. It is a board-level across industries, grounding the analysis in what is strategic concern for every organization that relies happening in practice. on a healthy talent pipeline and a workforce ready to make the most of Al’s potential. Strong entry­ -level pathways in particular matter for economic mobility, civic participation, and the broad- based prosperity that sustains stable, cohesive communities. Our choices will shape how quickly we reach the opportunities and overcome the challenges of this transition.\n\n3","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-3","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"3e6c619ed024ad954a045e5a401ccad2450a83f991aa29b6c39fe58213f1f4a3","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":6,"page":4,"heading":"AI와 초기 경력 일자리의 미래 · 4쪽","text":"Executive summary\n\nArtificial intelligence (AI) is reshaping work, and as Agriculture, Construction and Food Services are\n this is most visible at the entry level. Globally, comparatively less affected. How these roles and\n more than one in three (37%) young workers are pathways evolve will have significant implications for\n employed in occupations with medium to high organizational performance, workforce participation\n exposure to AI-driven task change, including three and economic mobility. This report introduces a\n in four young workers in Eastern Asia (75%) and framework across four dimensions – job access,\n two in three young workers in Northern America job design, talent pipelines and education system\n (69%) and Europe (63%). Sectors with the highest alignment – to help stakeholders identify where strain\n exposure include Financial Services, Information and is emerging, where deliberate action is needed and\n Communication, Professional Services, Science and what objectives leaders should prioritize in practice.\n Education, whereas entry-level roles in sectors such","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-4","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"dc7cf2d4f32326650d2354995a4052af67aab133b50119c548b5f439ac92624f","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":7,"page":4,"heading":"AI와 초기 경력 일자리의 미래 · 4쪽","text":"Executive summary: Framework for safeguarding and reinventing early career pathways\n\nDimension Key findings Priority objectives for action\n\nJob access Finding 1: Current hiring slowdowns at entry- Make entry-level hiring an explicit component\n level are evident. AI’s role remains contested. of strategic workforce planning, with clear\nSafeguarding continued Recent research suggests current slowdowns are targets to maintain or grow intake alongside\ncreation of entry-level most pronounced in occupations with higher AI AI adoption, and avoid reinforcing unintended\njobs exposure, but future expectations among employers disparities in access to early career pathways.\n and entry-level workers reveal a more nuanced\n outlook.\n\nFinding 2: Proactive support mechanisms may\n be needed to mitigate risks of AI reinforcing\n existing disparities in access to entry-level\n opportunities. More than 20% of entry-level\n workers are changing careers, re-entering the\n workforce or moving into new industries later in life.","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-4","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"57c2c7e3d5d0842d1855bf5e4f7575083d4b7a440ba944ce1b438bd069646eeb","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":8,"page":4,"heading":"AI와 초기 경력 일자리의 미래 · 4쪽","text":"Job design Finding 3. Organizations may need to manage Establish clear models for effective AI-enabled\n trade-offs between short-term efficiency job redesign, leveraging entry-level roles to\nEnsuring design of improvements, capability-building and work continue building critical skills and capabilities,\nentry-level jobs is fit for quality. 68% of entry-level workers report having rather than simply layering AI onto existing ways\npurpose seen an increase in productivity due to AI, but 45% of working.\n also spend more time working in general as a result\n of AI.\n\nFinding 4: Job redesign is emerging\n as a strategic lever of organizational\n competitiveness, but clear models for entry-\n level roles design are often still lacking.\n Companies with the strongest AI-driven financial\n outcomes are twice as likely to redesign workflows,\n yet conceptualizing what effective AI-enabled job\n redesign looks like remains a challenge, particularly\n at the early career stage.\n\nArtificial Intelligence and the Future of Entry-Level Work 4","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-4","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"fa8e89381efbe4b8e57fd6085475a3b11741d73d554a5e9d37ff1425f95bc8d0","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":9,"page":5,"heading":"AI와 초기 경력 일자리의 미래 · 5쪽","text":"Dimension Key findings Priority objectives for action\n\nTalent pipelines Finding 5: Efforts to reshape organizational Move from fixed role-based workforce\n structures are often focused on the base of the structures and job architectures towards more\nReinventing career hierarchy. Twenty-three percent of CEOs believe capability-based models of talent development,\npathways and capability present organizational structures are constraining ensuring talent pipelines are intentionally\ndevelopment as work performance, with attention falling on entry-level designed and talent is matched proactively to\nevolves roles. Expectations of AI-related structural change evolving roles.\n at the entry-level are almost twice as high as those\n for mid- or senior-level roles, with three-quarters of\n leaders expecting significant realignments.","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-5","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=5","page":5},"trust":"source-data-not-instructions"},{"id":"9432ac94246732ce20eaeb3ca4a994259eb23e2ac54bab13865dbb63e437499b","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":10,"page":5,"heading":"AI와 초기 경력 일자리의 미래 · 5쪽","text":"Finding 6: Organizational capability may be\n increasingly built through non-linear movement\n and exposure, not hierarchical sequence. While\n this creates new opportunities to build skills faster\n and more flexibly, entry-level workers continue to\n look for traditional signals of advancement, with\n 31% planning to ask for a promotion in the next\n year, underlining the importance of redesigning how\n to define and communicate progression in practice.","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-5","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=5","page":5},"trust":"source-data-not-instructions"},{"id":"05c73836a0cf649ec4aa225b74ce15b5bef7e06e9cfc144e7d7fa544264bd5d2","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":11,"page":5,"heading":"AI와 초기 경력 일자리의 미래 · 5쪽","text":"Education system Finding 7: Entry-level skills requirements are Build more continuous and responsive alignment evolving faster than current education systems alignment between employers, educators can keep pace. Entry-level roles in the highest AI- and policy-makers, ensuring curricula reflect Equipping education exposure quartile exhibit nearly twice the rate of net and provide exposure to changing workplace and training to keep skills change than non-entry-level roles, with 28% technologies, and strengthen alternative pace with changing of entry-level workers believing that half or fewer of pathways into employment alongside traditional demands of the AI- their current skills will still be relevant in three years. degrees. enabled workplace Finding 8: New signals of job readiness and alternative pathways are needed alongside traditional degrees. While traditional degrees remain important, leaders increasingly highlight the need for additional signals of workforce readiness, including applied experience, real-world problem- solving and exposure to workplace technologies.","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-5","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=5","page":5},"trust":"source-data-not-instructions"},{"id":"dc2ba05881905555697e67e327d191521955cff716e7c21389fa30aecb3fd94b","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":12,"page":5,"heading":"AI와 초기 경력 일자리의 미래 · 5쪽","text":"This is increasing interest in work-integrated learning and alternative pathways into employment.\n\nArtificial Intelligence and the Future of Entry-Level Work 5","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-5","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=5","page":5},"trust":"source-data-not-instructions"},{"id":"9ac1488f5201f1adfd930c589681e69bee72bfa798609068c0446d8bfc0bbaf1","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":13,"page":6,"heading":"AI와 초기 경력 일자리의 미래 · 6쪽","text":"1 Introduction:\n Context and framework","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-6","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=6","page":6},"trust":"source-data-not-instructions"},{"id":"4f7b623ef3eb371f753cea67369960b3db6bd9bef8e01658c806bc0289ef7752","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":14,"page":6,"heading":"AI와 초기 경력 일자리의 미래 · 6쪽","text":"Entry-level roles have long provided ordered pathways base of organizational hierarchies. Throughout this into paid work and onto the first step of traditional report, the term “early career” is sometimes used career ladders. Across economies, these roles more broadly to describe workers in the earlier stages play a critical part in workforce participation and of their careers, reflecting the way labour-market skill formation, offering structured opportunities to datasets are often grouped by age or tenure rather build practical experience and develop professional than organizational role. In many industries, entry-level capability. roles support day-to-day operations while providing a foundation for professional development and helping Globally, it is estimated that over 500 million young sustain future talent pipelines. people age 15–24 participate in the labour force today1 and over 600 million additional jobs will need to Analysis for this report estimates that, globally, more be created, predominantly in emerging economies, to than one-third of young workers (37%) are employed","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-6","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=6","page":6},"trust":"source-data-not-instructions"},{"id":"aedc13eae2e9770cc3304c55879e684dde579e3eb4b41317ad29d7e19b047e2b","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":15,"page":6,"heading":"AI와 초기 경력 일자리의 미래 · 6쪽","text":"keep up with demand from young people entering the in occupations with medium to high exposure to labour market by 20302. AI-driven task change, including three in four young workers in Eastern Asia and two in three in both Entry-level roles are typically defined by limited Northern America and Europe (see Figure 1). experience requirements and their position at the\n\nF I G U R E 1 Distribution of young workers (age 15–24) across high-, medium- and low-AI exposure\n occupations, by region\n\nEastern Asia 33.3% 42.4% 24.3%\n Northern America 23.4% 46.4% 30.2%\n Europe 22.4% 40.9% 36.7%\n Oceania 16.3% 41.5% 42.2%\nLatin America and the Caribbean 16.3% 35.0% 48.7%\n Central Asia 11.0% 27.0% 62.0%\n South-eastern Asia 9.9% 28.6% 61.5%\n Southern Asia 7.9% 16.9% 75.1%\n Middle East and Northern Africa 7.4% 25.0% 67.6%\n Sub-Saharan Africa 2.4% 17.2% 80.3%\n\n0% 20% 40% 60% 80% 100%\n\nExposure: High Medium Low","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-6","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=6","page":6},"trust":"source-data-not-instructions"},{"id":"4cba5810e5018fee46124f2c34dba6106fda59047bf73749ef6062d47dfb5a2e","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":16,"page":6,"heading":"AI와 초기 경력 일자리의 미래 · 6쪽","text":"Note: AI exposure is derived from the PwC AI Jobs Barometer at occupation level, averaged to ISCO-08 major groups and\n rescaled to 0–1. Exposure categories are defined using Jenks natural breaks to identify groupings in the distribution and mapped\n to ILOSTAT data to estimate the share of young workers (age 15–24) in each exposure group. ILOSTAT data series: Youth\n employment by sex, age and occupation (thousands) – Annual. Figures exclude ISCO-08 occupation “X: Not elsewhere classified”.\n Source: International Labour Organization, ILOSTAT & PwC 2026 AI Jobs Barometer.","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-6","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=6","page":6},"trust":"source-data-not-instructions"},{"id":"780844bcd76fee5e320bcedc1c474d2e21220ae2c64ba6fa15a745123f9c9378","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":17,"page":6,"heading":"AI와 초기 경력 일자리의 미래 · 6쪽","text":"These regional differences are partly driven by This is evident in the aforementioned regions, where\n variations in employment composition. At the sector larger shares of workers, including at entry level,\n level, AI exposure is concentrated in knowledge are employed in these sectors3. By contrast, young\n intensive industries, where entry level roles often workers in regions with high employment shares in\n involve routine, information processing tasks that sectors such as agriculture and construction remain\n are more susceptible to automation (see Figure 2). comparatively less exposed.\n\nArtificial Intelligence and the Future of Entry-Level Work 6","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-6","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=6","page":6},"trust":"source-data-not-instructions"},{"id":"ac3681cc628fe9dfadd5432c10a6fe0f5bbc509e0964945859dcf6db617cd03f","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":18,"page":7,"heading":"AI와 초기 경력 일자리의 미래 · 7쪽","text":"F I G U R E 2 AI exposure by sector and estimated number of young workers, age 15–24\n\nEstimated number of AI exposure ranking Sector young workers (age 15-24)\n\n1 Financial and Insurance Activities 4 million\n\n2 Information and Communication 6 million\n\n3 Professional, Scientific and Technical Activities 7 million\n\n4 Real Estate Activities 1 million\n\n5 Education 16 million\n\n6 Public Administration and Defence 8 million\n\n7 Mining and Quarrying 3 million\n\n8 Human Health and Social Work Activities 17 million\n\n9 Manufacturing 66 million\n\n10 Wholesale and Retail Trade 82 million\n\n11 Other Services and Household Activities 24 million\n\n12 Arts, Entertainment and Recreation 5 million\n\n13 Utilities and Infrastructure 13 million\n\n14 Construction 37 million\n\n15 Transportation and Storage 20 million\n\n16 Agriculture, Forestry and Fishing 159 million\n\n17 Accommodation and Food Service Activities 40 million\n\n18 Other & not elsewhere classified 29 million","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-7","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=7","page":7},"trust":"source-data-not-instructions"},{"id":"c61dbe4e363da63b9d418b1b6937e11c977216b8c1e0ae56d5d6698647b6687f","documentId":"f21cb9ce79142a5375a00a1e","documentSha256":"f21cb9ce79142a5375a00a1e529fc6e0414c9f65ef95c112b59012bc41f656b6","extractionVersion":"c177a4c7adae37fd4ea29534f2fa6f7fb6a754b2f861f52436da5f571e32523d","ordinal":19,"page":7,"heading":"AI와 초기 경력 일자리의 미래 · 7쪽","text":"Note: AI exposure is derived from the PwC AI Jobs Barometer and calculated as the employment-weighted average of occupa-\ntion-level AI exposure scores within each sector, based on the extent to which job tasks align with current AI capabilities. ILOSTAT\ndata series: Youth employment by sex, age and occupation (thousands) – Annual. Certain sectors have been grouped for\npresentation purposes. “Utilities & Infrastructure” includes electricity, gas, water supply, waste management and administrative\nsupport services. “Other Services and Household Activities” includes other service activities and household employer activities.\n“Other & not elsewhere classified” includes extraterritorial organizations and activities not elsewhere classified.\nSource: International Labour Organization, ILOSTAT & PwC 2026 AI Jobs Barometer.\n\nArtificial Intelligence and the Future of Entry-Level Work 7","citation":{"title":"AI와 초기 경력 일자리의 미래","publisher":"World Economic Forum","url":"/library/f21cb9ce79142a5375a00a1e#page-7","pdfUrl":"/library/f21cb9ce79142a5375a00a1e/original.pdf#page=7","page":7},"trust":"source-data-not-instructions"}]}