{"schemaVersion":"1.0","document":{"id":"4fb85d2a5824e7096a11c2fa","title":"생산성 도구에서 조직 전환으로","originalTitle":"AI at Work: From Productivity Hacks to Organizational Transformation","category":"ai","categoryLabel":"AI·에이전트","publisher":"World Economic Forum","language":"en","publicationYear":2026,"publicationMonth":1,"publishedOn":null,"datePrecision":"month","dateSource":"PDF 표지의 발행 연월","coverUrl":"/assets/covers/library-4fb85d2a5824e7096a11c2fa.jpg","tags":["조직","업무","생산성","AI 전환","productivity","organizational transformation"],"pages":26,"bytes":5880147,"sha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","searchable":true,"url":"/library/4fb85d2a5824e7096a11c2fa","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf","chunksUrl":"/api/library/4fb85d2a5824e7096a11c2fa/chunks","extraction":{"totalPages":26,"pagesWithSubstantialText":26,"sparsePages":[],"method":"pdf-text","ocrPerformed":false},"relatedPublications":[{"series":"커스텀 브리프","issue":"4호","url":"/archive/custom-04","title":"도입은 끝났다, 이제 출근시켜라"}],"metadataNote":"한국어 제목·분류·검색어는 원문 탐색을 위한 편집 정보입니다."},"extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","total":89,"offset":0,"nextOffset":20,"chunks":[{"id":"c48fe573e186dfa95ca44e855987dbc03f08f0c3697832098ac6510ad0e9d934","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":0,"page":1,"heading":"생산성 도구에서 조직 전환으로 · 1쪽","text":"C&T Industry Strategy Officers Community\n\nAI at Work:\nFrom Productivity\nHacks to Organizational\nTransformation\n\nC O M M U N I T Y P A P E R\nJ A N U A R Y 2 0 2 6","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-1","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=1","page":1},"trust":"source-data-not-instructions"},{"id":"ca1159407fe0429f1f2d8d2c5228b622d333d83f150554186109215b33d644b5","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":1,"page":2,"heading":"생산성 도구에서 조직 전환으로 · 2쪽","text":"Images: Getty Images, Unsplash\n\nContents\n\nForewords 3\n\nExecutive summary 5\n\nIntroduction 6\n\n1 The promise of AI 7\n\n2 The reality of AI 11\n\n2.1 The promise of AI is conditional 11\n\n2.2 Trust and governance 12\n\n2.3 Reshaping job tiers 13\n\n2.4 Uneven adoption 14\n\n3 The future of AI and work 16\n\n3.1 Four imperatives to support workers in adopting AI 16\n\n3.2 Three macro questions 19\n\nConclusion 20\n\nAppendix: Questions sent 21\n\nContributors 23\n\nEndnotes 25","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-2","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=2","page":2},"trust":"source-data-not-instructions"},{"id":"599f15babccc9efe36760e8ccdfd8a64bdff49da6ccaed69a8fd6d0c839964cd","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":2,"page":2,"heading":"생산성 도구에서 조직 전환으로 · 2쪽","text":"Disclaimer\nThis document is published by the\nWorld Economic Forum as a contribution\nto a project, insight area or interaction.\nThe findings, interpretations and\nconclusions expressed herein are a result\nof a collaborative process facilitated and\nendorsed by the World Economic Forum\nbut whose results do not necessarily\nrepresent the views of the World Economic\nForum, nor the entirety of its Members,\nPartners or other stakeholders.\n© 2026 World Economic Forum. All rights\nreserved. No part of this publication may\nbe reproduced or transmitted in any form\nor by any means, including photocopying\nand recording, or by any information\nstorage and retrieval system.\n\nAI at Work: From Productivity Hacks to Organizational Transformation 2","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-2","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=2","page":2},"trust":"source-data-not-instructions"},{"id":"1e6abe69276a8cc79daeebbc4161f9b14348ba9fe8490b16b941c52e30ab53a7","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":3,"page":3,"heading":"생산성 도구에서 조직 전환으로 · 3쪽","text":"January 2026 AI at Work:\n From Productivity Hacks to Organizational Transformation\n\nForeword\n\nErik Brynjolfsson\n Jerry Yang and Akiko Yamazaki Professor,\n Institute for Human-Centered Artificial Intelligence,\n Director of the Digital Economy Lab, Stanford University;\n Co-Chair, World Economic Forum Future of Jobs Initiative","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-3","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"2d894c5f74e824770594ab5f78de5d2fec28050bd44155ba2a1e966ef4c5a2d7","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":4,"page":3,"heading":"생산성 도구에서 조직 전환으로 · 3쪽","text":"AI at work: What the earliest signals are telling First, the risk. If you remove the first rung of the us – and what leaders need to do now career ladder, you are not just changing cost structure. You are potentially damaging your firm’s We are living through one of the most important talent pipeline. You are making it harder for the next transitions in the history of work. For decades, generation to acquire tacit knowledge, mentorship digital technologies have reshaped production, and judgement. Over time, that erodes managerial logistics, customer service and even strategy. But depth and strategic capacity. You cannot promote artificial intelligence – especially modern generative people who were never hired. AI – is different in both its speed and the scope of tasks it can take on. It is no longer limited to Second, the opportunity. The same tools that routine, codified work. It now reaches deeply into allow AI to handle first-draft work can, if deployed analytical, creative and communication tasks that thoughtfully, accelerate human development instead","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-3","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"390a38a199b7c051557e6ec9714ae7d9473586b7be025aeb0ad31cecd4e82dcf","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":5,"page":3,"heading":"생산성 도구에서 조직 전환으로 · 3쪽","text":"were historically considered the foundation of of replacing it. We are already seeing cases where early-career “knowledge work”. junior employees are brought into higher-value conversations earlier, supported by AI co-pilots and This community paper, produced in collaboration internal knowledge assistants. Rather than spending with leading technology and services firms that their first year formatting decks and responding to are both building and deploying AI at scale, offers tier-one tickets, they are sitting in on client meetings, a rare view inside that transition. It does not synthesizing options and exercising judgement – speculate about what AI might accomplish some years ahead of the old schedule. This model can day. It documents what is already happening produce not fewer skilled workers, but stronger ones. inside organizations today: how work is being redesigned, which skills are being repriced Which outcome you get is not determined by the and how leadership, not just technology, is technology. It is determined by leadership. determining who benefits.","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-3","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"03d17af7987fa439d5f00385d9a263ac9f47507a42611fb3258a5d8779e2840d","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":6,"page":3,"heading":"생산성 도구에서 조직 전환으로 · 3쪽","text":"That is, ultimately, the core message for business Leaders are discovering that AI can now perform leaders: the economic gains from AI will not come many of the traditional “first-rung” tasks that simply from “installing” a model. They will come from historically justified hiring a large class of junior redesigning workflows, incentives, management analysts, assistants, researchers and associates: practices, governance and upskilling pathways so draft the briefing; prepare the summary; generate that humans and AI together create more value the first pass at a marketing concept; triage the than either could alone. The same model, dropped customer ticket; build the slides; do the first into two different firms, can be either a demo or a compliance check. Those tasks are no longer the transformation. The difference is organizational. exclusive domain of entry-level hires. This is why I have argued for years that the This has two profound implications. real bottleneck in the digital economy is not invention – it is diffusion. We are quite good,","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-3","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"50ac43d76b7918e9181c9caab4d8d7eae752e3867524ec3080af6a94ca1e6255","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":7,"page":3,"heading":"생산성 도구에서 조직 전환으로 · 3쪽","text":"AI at Work: From Productivity Hacks to Organizational Transformation 3","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-3","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=3","page":3},"trust":"source-data-not-instructions"},{"id":"30d352c8760798561d2ce3b5191b3a71a53e213a3d9a94ecbdd2ff34954a0b75","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":8,"page":4,"heading":"생산성 도구에서 조직 전환으로 · 4쪽","text":"as a society, at producing powerful technologies. Finally, we cannot navigate what we cannot We are much less good at translating those measure. One of the reasons why data from payroll technologies into broad-based productivity platform ADP and other high-frequency sources is growth, higher wages and shared prosperity. That so important is that they let us move beyond static, translation challenge is one of the reasons I helped backward-looking averages. They let us see, almost start Workhelix. Our focus is to help companies in real time, where employment is tightening, where identify specific workflows where AI can augment opportunity is expanding, and where pressure workers, boost measurable performance and is building. That kind of visibility is essential for create durable competitive advantage – not responsible leadership. It allows us to respond just cut short-term labour costs. The goal is early, not after the damage is done. empowerment, not hollowing out. The story of AI and work is not prewritten. We can","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-4","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"ed272232b76c92e90de7f6b190c800d6f28a6ab5e5e5aff94aa76a1fecd41ad6","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":9,"page":4,"heading":"생산성 도구에서 조직 전환으로 · 4쪽","text":"It is also why skills are now the strategic currency choose an outcome in which AI amplifies human of the firm. In my role co-chairing the World capability, accelerates learning, improves service Economic Forum’s Future of Jobs efforts, we quality, raises productivity and supports broadly have emphasized that organizations cannot treat shared prosperity. Or we can choose an outcome skills development as an afterthought or an HR in which AI quietly erodes access to economic talking point. It is core infrastructure. The firms opportunity and concentrates gains narrowly. that will lead in the AI era are those that build systems for continuous reskilling, internal mobility The companies represented in this paper are and human–AI collaboration. They recognize that showing us, right now, what both paths look like. the half-life of many technical skills is shrinking, Our responsibility – as executives, policy-makers but the value of adaptability, judgement and and researchers – is to scale the path that creates domain expertise is rising. more value for more people.","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-4","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"991f1cf6678aaf73849a29353afe8320755fc2d947d7976bc94ad883cf9f5bd1","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":10,"page":4,"heading":"생산성 도구에서 조직 전환으로 · 4쪽","text":"Foreword from the community\n\nAnn Marie Lavigne\n Ravi Kiran Kuchibhotla\n Vice-President,\n Chief Strategy Officer,\n Strategic Initiatives,\n Cognizant\n Snowflake","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-4","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"decb996047a06dc81dd4e39a21a2931b7f02ad83d8933360a17ee34c1c821965","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":11,"page":4,"heading":"생산성 도구에서 조직 전환으로 · 4쪽","text":"The world is moving rapidly from theoretical We recognize that workers across industries are debates about artificial intelligence to the lived understandably anxious about what AI means for reality of its impact on work. Today, organizations their jobs and futures. Therefore, as tech leaders, are no longer asking “if” AI will change how work we have a responsibility to ensure this transition gets done; they are experiencing at first hand how is inclusive, human-centred, and focused on it is reshaping roles, workflows and the very fabric creating meaningful, fulfilling work. Our technology of their enterprises. This paper captures a unique development and deployment must go hand in hand front-line perspective from leaders across the sector with investing in digital skills, ethical standards and who are not only developing the technology but supportive organizational cultures. also experimenting, learning and adapting their own workforces to an AI-augmented reality. But the future of work is not a challenge for the C&T industry alone. It requires ongoing dialogue","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-4","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"6b39c8d888e797f4989e86b8e13132dc0327751b22abee75dcdd48941bd1eebe","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":12,"page":4,"heading":"생산성 도구에서 조직 전환으로 · 4쪽","text":"Our experience, and those of our colleagues who and partnership between business, government, contributed to this paper, shows that the promise academia and civil society. This paper is a of AI is not about replacing people with machines. contribution to that dialogue, providing a candid Instead, it is about reimagining how human and look at how the transformation of work is already digital capabilities work together. The examples unfolding, and what we must do to guide it wisely. highlighted here demonstrate that success in What is clear from the experiences shared here is realizing AI’s full potential demands a fundamental that leadership, learning and responsible innovation redesign of workflows, a commitment to reskilling will determine whether AI becomes a driver of shared people and a deep focus on embedding trust and prosperity or division. governance into every layer of the organization. We hope you enjoy reading this paper and find its As members of the World Economic Forum’s C&T insights valuable as you navigate the opportunities","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-4","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"ae76f58ab815587f76e1a43c0df9912dd626bce3e222de6dd741b83c8a9bc8b4","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":13,"page":4,"heading":"생산성 도구에서 조직 전환으로 · 4쪽","text":"Strategy Officers community, we are united by and challenges of the intelligent age. optimism about AI’s potential, but also by realism about the complexity of putting it into practice.\n\nAI at Work: From Productivity Hacks to Organizational Transformation 4","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-4","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=4","page":4},"trust":"source-data-not-instructions"},{"id":"62f14a1f6e8099df52dbf7c12b8d51fa81633c55e46aacc56be454f5cd97567c","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":14,"page":5,"heading":"생산성 도구에서 조직 전환으로 · 5쪽","text":"Executive summary\nArtificial intelligence is shifting from\npilots and productivity hacks into the\nfoundational operation of companies.\n\nThree years after the release of ChatGPT, many – Job hierarchies are shifting in unexpected\n firms are still in the early stages of adoption, but the ways. Routine starter tasks are being automated,\n experiences of technology firms offer a rare insider’s but greater vulnerability may lie in mid-career\n view of how AI is changing work. coordination roles, not at the entry level.","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-5","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=5","page":5},"trust":"source-data-not-instructions"},{"id":"48bafd78a748df90b8e5724d7d144b545d12fd21da384e1d7cff03894c161398","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":15,"page":5,"heading":"생산성 도구에서 조직 전환으로 · 5쪽","text":"Supported by concrete examples of artificial – Cultural dividends may be as valuable\n intelligence (AI) use cases across functions and as productivity. Business leaders have\n industries, these insights shift the narrative from seen reduced burn-out, faster learning and\n theory to reality. They confirm several familiar greater employee engagement when AI was\n themes, including automation of routine tasks, integrated into work.\n augmentation of professional roles and the\n creation of new AI-native jobs – where AI is an – Adoption is advancing unevenly. Large\n intrinsic, foundational component of the job’s enterprises drive frontier experimentation, while\n core functionality. They also challenge some smaller firms and emerging markets may leapfrog\n conventional wisdom. Key takeaways include: with inventive, context-specific applications.","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-5","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=5","page":5},"trust":"source-data-not-instructions"},{"id":"b0944588fbe64bddb54dca30039a78179684f1e08b57e7017f4e881ab3a2a444","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":16,"page":5,"heading":"생산성 도구에서 조직 전환으로 · 5쪽","text":"– Scaling is as much an organizational feat These findings are early signals rather than settled\n as a technical one. Success depends on outcomes. But they point executives towards the\n high-quality data, governance, organizational long-tail, high-impact questions that could shape the\n redesign and integration into workflows; future of work: how to redesign career trajectories,\n without those pieces, AI risks becoming a how to measure and sustain cultural gains, how to\n costly distraction. embed accountability into AI systems and how to\n adapt strategies across diverse global contexts.\n\nAI at Work: From Productivity Hacks to Organizational Transformation 5","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-5","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=5","page":5},"trust":"source-data-not-instructions"},{"id":"475a7db385078d896d96910a17eede95607262976d82da0d349deebb2d0b0117","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":17,"page":6,"heading":"생산성 도구에서 조직 전환으로 · 6쪽","text":"Introduction\nIn the three years since ChatGPT was\nlaunched, how AI will affect the workplace\nremains a polarizing question.","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-6","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=6","page":6},"trust":"source-data-not-instructions"},{"id":"2e1ab0b37335265602b862102ae83217f88f9b7ff454f72b75c997b0f299adf9","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":18,"page":6,"heading":"생산성 도구에서 조직 전환으로 · 6쪽","text":"Utopian visions cast AI as a limitless productivity 2. The reality examines how firms grapple with engine. Pessimistic narratives warn of widespread scaling bottlenecks, the experience of workers job losses and social disruption. Much of the public and organizational blind spots. conversation is caught between these extremes. Even scholarly and industry studies, while more 3. The future looks at immediate action items for measured, tend to analyse AI at a distance – by organizations adopting AI, and large questions modelling its potential impacts or extrapolating from that remain unanswered. It also highlights the surveys – rather than tracing the lived experience of responsibility of the tech sector to support companies on the frontier. workers in all industries in making this transition and to create economic opportunities for all. This community paper tries to add a different vantage point. It draws on the experiences of more than 20 Companies in the community acknowledge that leading technology firms across three regions that some of their findings are anecdotal and require","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-6","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=6","page":6},"trust":"source-data-not-instructions"},{"id":"69b700f6500ffb0fa5d7bb7f5e1cb24b19bcab7e982d18567189e7e91db23d54","documentId":"4fb85d2a5824e7096a11c2fa","documentSha256":"4fb85d2a5824e7096a11c2fa8d970e3b5a4a778f7479f557f82b57ac792da107","extractionVersion":"6b215fe23ee93e9cc8d8915aefd4c7f8c0946cb58476a0237ec6d3c136200ba2","ordinal":19,"page":6,"heading":"생산성 도구에서 조직 전환으로 · 6쪽","text":"are not only building AI tools but also deploying them more depth and systemic measurement. But for at scale within their own organizations and their decision-makers both inside and outside the tech clients.1 Their perspective provides a rare insider’s sector, these lessons matter. They suggest that AI’s view: what happens when AI moves beyond pilots impact on work will not be determined by technical and individualized usage to become part of the capability alone, but by how organizations imagine, scaffolding of the enterprise itself? What promises do measure and govern the new systems they are now companies see, what realities do they confront and building. This transition is redefining how people what futures are they beginning to design? work, learn and lead and so the real story of AI is about human, not technological, transformation. To bring structure to these insights, the paper proceeds in three stages:\n\n1. The promise explores AI’s potential to\n collaborate and orchestrate tasks at various\n workplaces, with benefits extending beyond\n productivity into innovation and culture.","citation":{"title":"생산성 도구에서 조직 전환으로","publisher":"World Economic Forum","url":"/library/4fb85d2a5824e7096a11c2fa#page-6","pdfUrl":"/library/4fb85d2a5824e7096a11c2fa/original.pdf#page=6","page":6},"trust":"source-data-not-instructions"}]}