{"id":7491,"date":"2026-03-14T15:56:32","date_gmt":"2026-03-14T14:56:32","guid":{"rendered":"https:\/\/www.htt.it\/?p=7491"},"modified":"2026-03-21T12:05:00","modified_gmt":"2026-03-21T11:05:00","slug":"anthropic-and-ai-in-the-workplace-young-people-at-risk","status":"publish","type":"post","link":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/","title":{"rendered":"Anthropic and AI in the workplace: young people at risk"},"content":{"rendered":"\n\n<!-- SECTION -->\n<section  class=\"   whitesection\" style=\"\">\n    <div class=\"testo-colonna-centrale htt-generic-text\">\n        <div class=\"htt-container\">\n                    <\/div>\n    <\/div>\n<\/section>\n\n\n\n\n<!-- SECTION -->\n<section  class=\"   whitesection\" style=\"\">\n    <div class=\"testo-colonna-centrale htt-generic-text\">\n        <div class=\"htt-container\">\n            <article class=\"htt-article htt-article--anthropic-labor\" role=\"article\" aria-labelledby=\"article-title\">\n<header class=\"htt-article__header\">\n<p class=\"htt-article__eyebrow\">AI, Work &amp; Organization<\/p>\n<h2 id=\"article-title\" class=\"htt-article__title\">Anthropic, AI and work: the real risk is not mass unemployment, but the collapse of junior work<\/h2>\n<p class=\"htt-article__subtitle\">Anthropic\u2019s new study on AI in the workplace says that AI is not yet causing unemployment to surge. But stopping there would be a mistake: the most important signal concerns hiring, training, and access to professions. And it is a far more structural signal than it may seem.<\/p>\n<p>\n  We had already reflected on this topic in our in-depth article on<br \/>\n  <a href=\"https:\/\/www.htt.it\/il-futuro-del-lavoro-con-lintelligenza-artificiale-ia-nuove-opportunita-e-sfide-da-affrontare\/\"> how artificial intelligence is changing the future of work<br \/>\n  <\/a>, but Anthropic\u2019s report adds a more specific element: the possible impact on junior work and on the development of skills.\n<\/p>\n<\/header>\n<nav class=\"htt-article__toc\" aria-labelledby=\"toc-title\">\n<h2 id=\"toc-title\" class=\"htt-article__toc-title\">In this article<\/h2>\n<ol class=\"htt-article__toc-list\">\n<li><a href=\"#perche-conta\">What Anthropic\u2019s report measures about AI and work<\/a><\/li>\n<li><a href=\"#cosa-dice-report\">What Anthropic says<\/a><\/li>\n<li><a href=\"#lavoratori-esposti-title\">Which workers are currently most exposed to AI?<\/a><\/li>\n<li><a href=\"#accesso-lavoro\">Why AI may hit junior work first<\/a><\/li>\n<li><a href=\"#limite-metodologico\">The limits of the Anthropic report: method, scope and bias<\/a><\/li>\n<li><a href=\"#alta-esposizione\">Why high exposure to AI does not automatically mean less work<\/a><\/li>\n<li><a href=\"#punto-cieco\">How is AI changing internal training?<\/a><\/li>\n<li><a href=\"#visioni-leader-ai\">The most radical visions: Elon Musk and Sam Altman on the future of work<\/a><\/li>\n<li><a href=\"#conclusioni\">Conclusions<\/a><\/li>\n<li><a href=\"#faq\">FAQ<\/a><\/li>\n<li><a href=\"#bibliografia\">Bibliography<\/a><\/li>\n<\/ol>\n<\/nav>\n<section id=\"perche-conta\" class=\"htt-article__section\" aria-labelledby=\"perche-conta-title\">\n<h2 id=\"perche-conta-title\">What Anthropic\u2019s report measures about AI and work<\/h2>\n<p>When it comes to artificial intelligence and the labor market, public debate still tends to swing between two opposite extremes. On the one hand, there is the apocalyptic narrative: millions of jobs wiped out, professions made obsolete, offices emptied out. On the other, there is the reassuring reflex: AI helps, speeds things up, suggests, but in the end does not really change employment balances.\n    <\/p>\n<p>\nAnthropic\u2019s report <em>Labor market impacts of AI: A new measure and early evidence<\/em> is interesting precisely because it tries to move beyond this polarization. Its value, however, lies not only in the answer it offers, but in the question it forces us to ask: <strong>is AI eliminating jobs, or is it transforming the way people enter work, grow within organizations, and build the skills of the future?<\/strong>\n    <\/p>\n<p>\nThis is the most useful perspective from which to read the report: not only as a snapshot of employment, but as an early indicator of a broader transformation affecting team structures, internal training, seniority composition, and organizational models.\n    <\/p>\n<\/section>\n<section class=\"htt-definition-box\" aria-label=\"Key takeaway\">\n<p>\n    <strong>The key point not to miss:<\/strong><br \/>\n    the most underestimated risk is not immediate mass unemployment, but a progressive compression of entry-level work. If junior roles are reduced, the pipeline that forms tomorrow\u2019s senior professionals is weakened.\n  <\/p>\n<\/section>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ufficio-del-futuro-htt-lavoro-ai-300x167.jpg\" alt=\"The future of work between AI, automation and the transformation of professions\" width=\"300\" height=\"167\" class=\"aligncenter size-medium wp-image-7463\" srcset=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ufficio-del-futuro-htt-lavoro-ai-300x167.jpg 300w, https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ufficio-del-futuro-htt-lavoro-ai-1024x571.jpg 1024w, https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ufficio-del-futuro-htt-lavoro-ai.jpg 1400w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<section class=\"htt-insight-box htt-insight-box--author\" aria-labelledby=\"author-thought-title\">\n<h2 id=\"author-thought-title\" class=\"htt-insight-box__title\">A decisive difference compared with previous industrial revolutions<\/h2>\n<p>A necessary premise must be made first.<br \/>\nThere is one aspect that makes the AI revolution different from many of the previous ones: it affects the current generation directly, not only the next one.\n    <\/p>\n<p>\nTo simplify with an example: during the first industrial revolution, a father working in the fields with a mule could, at least in many cases, continue doing that job for years.<br \/>\n  The deepest change in the way work was done mainly emerged in the next generation, which grew up in a world already transformed by machines, factories, and a new productive model.\n    <\/p>\n<p>\nWith artificial intelligence, something different is happening. The change does not only affect those who will enter the labor market tomorrow, but also those who are already in it today.<br \/>\nThere is no generation that observes and another that inherits: there are professionals, office workers, technicians, managers and creatives who must adapt immediately, while the change is already underway.\n    <\/p>\n<p>\nThis is one of the most radical elements of AI: it does not ask the children to learn a new profession, but the parents to rethink their own. And that is our starting point.\n    <\/p>\n<\/section>\n<section id=\"cosa-dice-report\" class=\"htt-article__section\" aria-labelledby=\"cosa-dice-report-title\">\n<h2 id=\"cosa-dice-report-title\">What Anthropic says<\/h2>\n<p>The core of the report is a new metric called <strong>observed exposure<\/strong>.<br \/>\nIn essence, Anthropic combines two levels of analysis: on the one hand, the theoretical feasibility of a task using large language models; on the other, real-world use observed in work contexts. The goal is to distinguish <strong>what AI <em>could<\/em> do<\/strong> from <strong>what it is <em>already doing, in other words its actual adoption in work settings<\/em><\/strong>.\n    <\/p>\n<p>\nThis is an important distinction. Over the last two years, many analyses have reasoned mainly in terms of theoretical potential, fueling very drastic interpretations. Anthropic instead tries to introduce a more concrete criterion: it is not enough to know that an activity is technically automatable, you also need to understand whether that automation is actually showing up in professional workflows.\n    <\/p>\n<p>\nThe results are already enough to correct some widespread simplifications. The most exposed occupations do not coincide with manual work or with roles traditionally seen as weaker. Instead, many cognitive, office-based, digital and language-heavy professions emerge: programmers, customer service representatives, data entry workers, medical documentation specialists, market analysts, financial roles and technical support roles.\n    <\/p>\n<p>\nThe point, then, is not qualification in the traditional sense, but how much activities can be <strong>described, standardized, and made formalizable<\/strong>. Generative AI enters more easily where there are digital, structured, repetitive, describable and verifiable tasks. And this affects many jobs that for years were assumed to be too complex to be truly touched.\n    <\/p>\n<p>\n  It is no coincidence that this impact is concentrated above all in cognitive, language-based and structured activities. It is a theme we had already touched on in the article <a href=\"https:\/\/www.htt.it\/come-lintelligenza-artificiale-lavora-con-il-nostro-cervello\/\">How artificial intelligence works with our brain<\/a>, which shows how AI is already changing the way we learn, work and make decisions.\n<\/p>\n<p>\nAnother relevant aspect is the gap between technical capability and actual use. In several occupational categories, the potential of the models is far higher than their concrete adoption in companies. This may seem reassuring, but if read carefully it says something else: not that the risk is lower, but that the transformation is still in its absorption phase.\n    <\/p>\n<\/section>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/capacita-teorica-lavoro-ai-300x300.webp\" alt=\"Theoretical capability and observed exposure by occupational category.\" width=\"300\" height=\"300\" class=\"aligncenter size-medium wp-image-7457\" srcset=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/capacita-teorica-lavoro-ai-300x300.webp 300w, https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/capacita-teorica-lavoro-ai-1024x1024.webp 1024w, https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/capacita-teorica-lavoro-ai-150x150.webp 150w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<section class=\"htt-insight-box\" aria-label=\"Critical insight\">\n<h2 class=\"htt-insight-box__title\">The most important insight<\/h2>\n<p>\nThe fact that AI can do more than companies are already using does not reduce the scale of the phenomenon. It suggests, rather, that we are still in its early stage. First, processes change; then hiring policies; then team architecture. Only afterward does the change become mature enough to appear clearly in macro-level numbers.\n    <\/p>\n<\/section>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/crescita-occupazione-2024-2034-vs-ai-exposure-300x169.webp\" alt=\"Projected BLS employment growth from 2024 to 2034 versus observed exposure\" width=\"300\" height=\"169\" class=\"aligncenter size-medium wp-image-7459\" srcset=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/crescita-occupazione-2024-2034-vs-ai-exposure-300x169.webp 300w, https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/crescita-occupazione-2024-2034-vs-ai-exposure-1024x576.webp 1024w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<section class=\"htt-article__section\" aria-labelledby=\"lavoratori-esposti-title\">\n<h2 id=\"lavoratori-esposti-title\">Which workers are currently most exposed to AI?<\/h2>\n<p>\n    Anthropic\u2019s report shows that the workers most exposed to artificial intelligence are not manual or lower-skilled workers, but many cognitive and office-based roles. At the top of the ranking are software programmers, with observed coverage of 74.5%, followed by customer service workers at 70.1%, data entry workers at 67.1%, and medical documentation specialists at 66.7%.\n  <\/p>\n<p>\n    At the opposite end, around 30% of workers show zero exposure. This group includes professions such as cooks, mechanics, lifeguards and bartenders: roles in which physical presence, direct interaction with people and environments, immediate adaptability and situational judgment matter. These are activities that, at least for now, cannot easily be absorbed by a language model.\n  <\/p>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/differenze-esposizione-fra-lavoratori-300x169.webp\" alt=\"Differences between workers with high and low exposure, Current Population Survey\" width=\"300\" height=\"169\" class=\"aligncenter size-medium wp-image-7470\" srcset=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/differenze-esposizione-fra-lavoratori-300x169.webp 300w, https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/differenze-esposizione-fra-lavoratori-1024x576.webp 1024w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>\n    There is another point worth noting. The workers most exposed to AI tend to be more often women, more educated, better paid and on average older. This makes the picture even more interesting, because it challenges one of the most superficial narratives about automation: it is not primarily the profiles traditionally considered most fragile that are at the center of the initial impact, but many professions belonging to structured cognitive work.\n  <\/p>\n<p>\n    This is precisely one of the report\u2019s most relevant aspects: AI is not primarily hitting low-paid or traditionally \u201croutine\u201d work, but rather activities that can be codified, standardized and turned into predictable operational flows. And this makes simplistic readings of AI disruption in the labor market much harder to sustain.\n  <\/p>\n<\/section>\n<section id=\"accesso-lavoro\" class=\"htt-article__section\" aria-labelledby=\"accesso-lavoro-title\">\n<h2 id=\"accesso-lavoro-title\">Why AI may hit junior work first<\/h2>\n<p>One of the most cited passages of the report concerns the fact that, at least for now, there is no strong evidence of a systematic increase in unemployment among the most exposed occupations. This is a useful point and deserves attention, but it is not the most interesting one.\n    <\/p>\n<p>\nThe most delicate signal, within the group considered by Anthropic, concerns young people between the ages of 22 and 25. In high-exposure occupations, Anthropic observes a decline in entry into new jobs compared with 2022. The authors of the report themselves urge interpretative caution, and rightly so, but the direction of the signal is already significant.\n    <\/p>\n<p>\nHere lies the report\u2019s most interesting and also most critical reading: <strong>AI may not immediately destroy existing jobs, but it may compress access to future jobs<\/strong>. And that is a much less visible, much slower, but also much more structural impact.\n    <\/p>\n<p>\nIf a company can produce the same output with five seniors supported by AI instead of five seniors plus two juniors, it does not necessarily have to lay anyone off today: it can simply decide not to hire tomorrow. The problem is that if that junior never enters, they do not accumulate experience, they do not develop a craft, they do not acquire context, and they do not become the middle or senior professional of the day after tomorrow.\n    <\/p>\n<p>\nThis is where the issue moves beyond labor economics in the strict sense and becomes an organizational and training issue. It does not concern only the number of people employed, but the <strong>ability of a system to generate skills over time<\/strong>.\n    <\/p>\n<p>\nThis interpretation is also consistent with other empirical studies on generative AI at work. In several contexts, the main effect does not seem to be immediate substitution, but rather the redistribution of productivity and competence. This can help less experienced workers who are already in place, while at the same time reducing incentives to hire new entry-level profiles.\n    <\/p>\n<\/section>\n<section id=\"limite-metodologico\" class=\"htt-article__section\" aria-labelledby=\"limite-metodologico-title\">\n<h2 id=\"limite-metodologico-title\">The limits of the Anthropic report: method, scope and bias<\/h2>\n<p>A more critical perspective is needed here. The report is serious, well built, and more useful than a great deal of superficial commentary. But its main metric includes a structural limitation: part of the analysis is based on use cases observed within the Anthropic ecosystem.\n<\/p>\n<p>This means that <em>observed exposure<\/em> is not a perfectly neutral measure of the labor market as a whole. It is a measure mediated by a product, a user base, a usage logic, and specific adoption patterns. Put even more directly: the report observes work through Claude\u2019s window.\n<\/p>\n<p>This is not a reason to dismiss it. On the contrary, its proximity to real usage data is precisely what makes it more interesting than many theoretical estimates. But it should not be turned into a definitive verdict. The real market is already multi-model, multi-tool and multi-process. Companies use ChatGPT, Copilot, Gemini, vertical agents, embedded tools inside work software, APIs, automations and proprietary stacks.\n<\/p>\n<p>There is also a second, even more substantial limitation. Professions are not simple sums of tasks, but combinations of execution, judgment, responsibility, coordination, context and trust. Automating one portion of work does not automatically mean replacing a role. Task analysis is extremely useful for understanding where AI enters, but much less sufficient for understanding where work truly disappears.\n<\/p>\n<p>\n  There is finally a third limitation to consider: the report mainly observes the U.S. labor market, which has historically been faster in adopting new technologies. In Italy, where the economic fabric is largely made up of small and medium-sized enterprises, it is plausible that the organizational adoption of AI will follow slower timelines. This does not reduce the report\u2019s relevance, but it does suggest reading its results as an early signal rather than as a picture immediately transferable to the Italian context.\n<\/p>\n<\/section>\n<section id=\"alta-esposizione\" class=\"htt-article__section\" aria-labelledby=\"alta-esposizione-title\">\n<h2 id=\"alta-esposizione-title\">Why high exposure to AI does not automatically mean less work?<\/h2>\n<p>Another important point in the report concerns the relationship between AI exposure and employment growth projections. The finding is interesting, but it should be read with caution. The risk of a mechanical interpretation is very high.\n    <\/p>\n<p>\nThe reason is simple: <strong>high exposure does not automatically equate to occupational decline<\/strong>. Some roles may be highly exposed and still continue to grow. In some cases, AI does not eliminate work, but changes its scope, organization and productivity. In other cases, it may even increase overall demand for that kind of function.\n    <\/p>\n<p>\nThis is particularly true for many technical, analytical and digital roles. The most frequent mistake is to confuse exposure with destiny. Measuring exposure is useful; using it as an automatic prophecy is wrong.\n    <\/p>\n<\/section>\n<section id=\"punto-cieco\" class=\"htt-article__section\" aria-labelledby=\"punto-cieco-title\">\n<h2 id=\"punto-cieco-title\">How is AI changing internal training?<\/h2>\n<p>The most underestimated part of this entire debate concerns the organization of work. Most companies are measuring AI through efficiency KPIs: time saved, tasks completed, content produced, tickets handled, cost reductions. These are understandable metrics, but they are not enough.\n    <\/p>\n<p>\n  If we want to read AI\u2019s impact properly, superficial metrics are not enough. We also discussed this in <a href=\"https:\/\/www.htt.it\/il-grande-inganno-delle-metriche-roas-ai-e-profitto-reale\/\">The great illusion of metrics: ROAS, AI and real profit<\/a>, where the point is precisely to distinguish between apparent signals and real impact on results.\n<\/p>\n<p>\nWhat many organizations are not yet measuring is the resilience of their own <strong>internal learning model<\/strong>. If junior activities are compressed, automated or absorbed by a few seniors supported by AI, how are tomorrow\u2019s professionals trained? Who will gain experience through simple but formative activities? Who will build the operational memory that today is acquired by correcting mistakes, observing seniors, managing repetitive cases and accumulating context?\n    <\/p>\n<figure class=\"htt-article__quote-wrap\">\n<blockquote class=\"htt-article__quote\">\n<p>\u201cIf you do not hire a junior today because you have AI, you will not have a senior tomorrow.\u201d<\/p>\n<\/blockquote><figcaption class=\"htt-article__quote-caption\">Sebastiano Barisoni, journalist and deputy editor-in-chief of Radio 24<\/figcaption><\/figure>\n<p>This is the real systemic risk. Not next quarter\u2019s payroll, but the quality of the skills pipeline in 2028, 2029 and 2030. AI does not just modify individual productivity. It reshapes the learning chain inside the company.\n    <\/p>\n<p>\nThat is why the most mature companies should begin asking more advanced questions: which roles are at risk of being hollowed out? Which seniority levels are we no longer cultivating? How is the balance between senior, middle and junior profiles changing? Which activities remain human because they depend on judgment, relationship, responsibility and context?\n    <\/p>\n<\/section>\n<section class=\"htt-article__section\" id=\"visioni-leader-ai\" aria-labelledby=\"visioni-leader-ai-title\">\n<h2 id=\"visioni-leader-ai-title\">The most radical visions: Elon Musk and Sam Altman on the future of work<\/h2>\n<p>\n    Alongside the data observed by Anthropic, it is worth considering the more radical predictions advanced by some of the key figures in the race for artificial intelligence. They help us understand the cultural and strategic climate in which today\u2019s debate on work is moving.\n  <\/p>\n<h3>Elon Musk: toward an economy in which work becomes optional<\/h3>\n<p>\n    Elon Musk describes an extremely far-reaching scenario. In his view, the combination of AI, humanoid robotics and abundant energy could lead, within a few years or decades, to a world in which human work is no longer an economic necessity, but a personal choice.\n  <\/p>\n<p>\n    It is a vision of near-total automation, in which the problem would no longer be finding work, but redefining the very meaning of work.\n  <\/p>\n<h3>Sam Altman: some jobs will disappear, but the system will reconfigure itself<\/h3>\n<p>\n    Sam Altman adopts a less utopian tone, but one that is no less disruptive. For some time he has argued that the shape of jobs will change profoundly, that some people will lose their roles, and that the relationship between capital, labor and social protection will have to be rethought.\n  <\/p>\n<p>\n    At the same time, he insists on the idea that we will not be facing occupational destruction alone, but also a redefinition of work: new tools, new functions and new economic activities will emerge precisely thanks to AI.\n  <\/p>\n<div class=\"htt-insight-box\" aria-label=\"Critical reading\">\n<h3 class=\"htt-insight-box__title\">The difference between prediction and evidence<\/h3>\n<p>\n      The decisive point is this: Musk\u2019s and Altman\u2019s visions should be read as strategic and political forecasts, not as empirical proof of what is already happening. This is precisely where Anthropic\u2019s report becomes useful: it brings the discussion back from the realm of radical declarations to that of observable signals.\n    <\/p>\n<p>\n      In other words, Musk and Altman reason about where AI could take us. Anthropic instead tries to measure where, concretely, AI is already beginning to intervene in the labor market.\n    <\/p>\n<\/p><\/div>\n<\/section>\n<section id=\"conclusioni\" class=\"htt-article__section\" aria-labelledby=\"conclusioni-title\">\n<h2 id=\"conclusioni-title\">Conclusions<\/h2>\n<p>\nAnthropic\u2019s merit is that it has brought the discussion about AI\u2019s impact on work back into a more measurable and less ideological framework. Its limitation is that it measures a transition that is still ongoing, and it measures it through a necessarily partial window. But that is precisely why the report is useful.\n    <\/p>\n<p>\nThe most superficial reading would say: AI is not causing mass unemployment, therefore the alarm is excessive. The more mature reading says something else: the change has already started, but it may show up first in processes and hiring, rather than in layoffs.\n    <\/p>\n<p>\nThe most serious impacts may not appear where everyone is looking. Not in the loudest headlines. Not in the immediate end of human work. But in the silent contraction of entry-level work, in the shrinking number of opportunities to learn, and in the transformation of a profession into a sequence of outputs governed by a few experts assisted by many models.\n    <\/p>\n<p>\nIf this reading is correct, then the most important question is not only how many jobs AI will destroy, but <strong>how many professionals it risks preventing from coming into being<\/strong>.\n    <\/p>\n<\/section>\n<section class=\"htt-article__section htt-article__section--final\" aria-labelledby=\"takeaways-title\">\n<h2 id=\"takeaways-title\">What should companies, HR teams and managers do in the face of AI?<\/h2>\n<p>\nThe smartest reaction is neither to deny AI\u2019s impact nor to chase a catastrophic narrative. More mature metrics need to be built. Not only productivity per worker, but also onboarding quality, learning speed, dependency on seniors, the rate of escalation toward humans, the resilience of internal training, and the ability to build competencies that are not based solely on execution.\n  <\/p>\n<p>\nThe issue is not man versus machine, but designing organizations and companies that know how to use AI without emptying out the path through which people are formed.\n  <\/p>\n<\/section>\n<section id=\"faq\" class=\"htt-faq\" aria-labelledby=\"faq-title\">\n<h2 id=\"faq-title\">FAQ<\/h2>\n<details>\n<summary>Does Anthropic\u2019s report say that AI is causing mass unemployment?<\/summary>\n<p>No. At least for now, the report does not show a systematic increase in unemployment in the most exposed occupations. The most delicate signal instead concerns the slowdown in young people entering some high-exposure jobs.<\/p>\n<\/details>\n<details>\n<summary>Which jobs are the most exposed according to Anthropic?<\/summary>\n<p>Among the most exposed roles are programmers, customer service representatives, data entry workers, medical documentation specialists, market analysts and financial profiles. More broadly, the activities most affected are cognitive, structured, digital and language-based ones.<\/p>\n<\/details>\n<details>\n<summary>What does observed exposure measure?<\/summary>\n<p>It is a metric that combines the theoretical possibility that a language model can perform a task with real-world use observed in work contexts. It is meant to distinguish AI\u2019s technical potential from its concrete adoption at work.<\/p>\n<\/details>\n<details>\n<summary>Why can the risk for juniors be more important than the unemployment figure?<\/summary>\n<p>Because a market that stops hiring entry-level profiles may appear stable in the short term, but in the medium term it weakens the skills pipeline, reduces professional mobility and makes the training of future senior profiles more fragile.<\/p>\n<\/details>\n<details>\n<summary>Does high exposure to AI mean a job will disappear?<\/summary>\n<p>No. Exposure is not destiny. Some roles will be compressed, others will be transformed, and others may still grow because AI increases their productivity or expands overall demand.<\/p>\n<\/details>\n<\/section>\n<section id=\"bibliografia\" class=\"htt-bibliography\" aria-labelledby=\"bibliography-title\">\n<h2 id=\"bibliography-title\">Bibliography<\/h2>\n<div class=\"htt-bibliography__grid\">\n<article class=\"htt-bibliography__card\">\n<h3>Anthropic Research<\/h3>\n<p><em>Labor market impacts of AI: A new measure and early evidence<\/em><\/p>\n<p><a href=\"https:\/\/www.anthropic.com\/research\/labor-market-impacts\" target=\"_blank\" rel=\"noopener noreferrer\">Open source<\/a><\/p>\n<\/article>\n<article class=\"htt-bibliography__card\">\n<h3>PDF Paper<\/h3>\n<p>Full version of the paper published by Anthropic.<\/p>\n<p><a href=\"https:\/\/cdn.sanity.io\/files\/4zrzovbb\/website\/3f7fd9d552e66269bdb108e207c5d80531d04b8b.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">Open PDF<\/a><\/p>\n<\/article>\n<article class=\"htt-bibliography__card\">\n<h3>NBER<\/h3>\n<p><em>Generative AI at Work<\/em>, Brynjolfsson, Li, Raymond.<\/p>\n<p><a href=\"https:\/\/www.nber.org\/papers\/w31161\" target=\"_blank\" rel=\"noopener noreferrer\">Open source<\/a><\/p>\n<\/article>\n<article class=\"htt-bibliography__card\">\n<h3>BLS<\/h3>\n<p>Employment Projections 2024\u20132034.<\/p>\n<p><a href=\"https:\/\/www.bls.gov\/news.release\/pdf\/ecopro.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">Open source<\/a><\/p>\n<\/article>\n<\/div>\n<\/section>\n<\/article>\n        <\/div>\n    <\/div>\n<\/section>\n\n\n\n<style>\n\/* =========================\n   HT&T Magazine Article CSS\n   Anthropic \/ Labor article\n   ========================= *\/\n\n.htt-article {\n  --htt-text: #0f172a;\n  --htt-text-soft: #334155;\n  --htt-muted: #64748b;\n  --htt-border: #d9e1ea;\n  --htt-border-strong: #c7d2df;\n  --htt-bg-soft: #f8fafc;\n  --htt-bg-accent: #eef6ff;\n  --htt-bg-highlight: #f4f7fb;\n  --htt-link: #0f172a;\n  --htt-link-hover: #2563eb;\n  --htt-radius: 18px;\n  --htt-radius-sm: 12px;\n  --htt-shadow: 0 12px 30px rgba(15, 23, 42, 0.06);\n  --htt-shadow-soft: 0 8px 18px rgba(15, 23, 42, 0.04);\n  --htt-max-width: 860px;\n\n  width: 100%;\n  max-width: var(--htt-max-width);\n  margin: 0 auto;\n  color: var(--htt-text);\n  font-size: 1.05rem;\n  line-height: 1.75;\n}\n\n.htt-article * {\n  box-sizing: border-box;\n}\n\n.htt-article__header {\n  margin-bottom: 2.5rem;\n}\n\n.htt-article__eyebrow {\n  margin: 0 0 0.85rem;\n  font-size: 0.82rem;\n  line-height: 1.3;\n  font-weight: 700;\n  letter-spacing: 0.08em;\n  text-transform: uppercase;\n  color: var(--htt-muted);\n}\n\n.htt-article__title,\n.htt-article h1 {\n  margin: 0 0 1rem;\n  font-size: clamp(2rem, 4.8vw, 3.6rem);\n  line-height: 1.05;\n  letter-spacing: -0.035em;\n  color: var(--htt-text);\n}\n\n.htt-article__subtitle {\n  margin: 0;\n  font-size: clamp(1.08rem, 2vw, 1.28rem);\n  line-height: 1.65;\n  color: var(--htt-text-soft);\n  max-width: 760px;\n}\n\n.htt-article__intro-note {\n  margin: 0 0 2rem;\n  padding: 1rem 1.2rem;\n  border: 1px solid var(--htt-border);\n  border-radius: var(--htt-radius-sm);\n  background: var(--htt-bg-soft);\n  color: var(--htt-text-soft);\n  font-size: 0.98rem;\n  line-height: 1.65;\n}\n\n\/* TOC *\/\n\n.htt-article__toc {\n  margin: 0 0 2.4rem;\n  padding: 1.35rem 1.4rem 1.25rem;\n  border: 1px solid var(--htt-border);\n  border-radius: var(--htt-radius);\n  background: #ffffff;\n  box-shadow: var(--htt-shadow-soft);\n}\n\n.htt-article__toc-title {\n  margin: 0 0 0.8rem;\n  font-size: 1.05rem;\n  line-height: 1.3;\n  color: var(--htt-text);\n}\n\n.htt-article__toc-list {\n  margin: 0;\n  padding-left: 1.2rem;\n}\n\n.htt-article__toc-list li {\n  margin: 0.35rem 0;\n  color: var(--htt-text-soft);\n}\n\n.htt-article__toc a {\n  color: var(--htt-link);\n  text-decoration: none;\n  border-bottom: 1px solid transparent;\n  transition: color 0.2s ease, border-color 0.2s ease;\n}\n\n.htt-article__toc a:hover,\n.htt-article__toc a:focus {\n  color: var(--htt-link-hover);\n  border-bottom-color: rgba(37, 99, 235, 0.35);\n  outline: none;\n}\n\n\/* Sections *\/\n\n.htt-article__section {\n  margin: 0 0 2.8rem;\n}\n\n.htt-article__section--final {\n  margin-top: 0.6rem;\n}\n\n.htt-article h2 {\n  margin: 0 0 1rem;\n  font-size: clamp(1.45rem, 2.8vw, 2.1rem);\n  line-height: 1.18;\n  letter-spacing: -0.025em;\n  color: var(--htt-text);\n}\n\n.htt-article h3 {\n  margin: 1.7rem 0 0.7rem;\n  font-size: 1.2rem;\n  line-height: 1.3;\n  color: var(--htt-text);\n}\n\n.htt-article p {\n  margin: 0 0 1.15rem;\n  color: var(--htt-text-soft);\n}\n\n.htt-article strong {\n  color: var(--htt-text);\n  font-weight: 700;\n}\n\n.htt-article em {\n  font-style: italic;\n}\n\n.htt-article a {\n  color: var(--htt-link);\n  text-decoration: underline;\n  text-decoration-thickness: 1px;\n  text-underline-offset: 0.16em;\n  transition: color 0.2s ease;\n}\n\n.htt-article a:hover,\n.htt-article a:focus {\n  color: var(--htt-link-hover);\n}\n\n\/* Blockquote *\/\n\n.htt-article blockquote {\n  margin: 1.7rem 0;\n  padding: 1.2rem 1.25rem 1.2rem 1.35rem;\n  border-left: 4px solid #2563eb;\n  border-radius: 0 14px 14px 0;\n  background: var(--htt-bg-soft);\n}\n\n.htt-article blockquote p:last-child {\n  margin-bottom: 0;\n  font-size: 1.02rem;\n  color: var(--htt-text);\n}\n\n\/* Definition box *\/\n\n.htt-definition-box {\n  margin: 2rem 0 2.5rem;\n  padding: 1.2rem 1.3rem;\n  border: 1px solid #cfe0f5;\n  border-radius: var(--htt-radius);\n  background: linear-gradient(180deg, #f8fbff 0%, #eef6ff 100%);\n  color: var(--htt-text-soft);\n  box-shadow: var(--htt-shadow-soft);\n}\n\n.htt-definition-box strong {\n  color: var(--htt-text);\n}\n\n\/* Insight box *\/\n\n.htt-insight-box {\n  margin: 2.2rem 0 2.6rem;\n  padding: 1.35rem 1.4rem;\n  border: 1px solid var(--htt-border-strong);\n  border-radius: var(--htt-radius);\n  background: var(--htt-bg-highlight);\n  box-shadow: var(--htt-shadow-soft);\n}\n\n.htt-insight-box__title {\n  margin: 0 0 0.6rem !important;\n  font-size: 1rem !important;\n  line-height: 1.3 !important;\n  letter-spacing: 0.04em;\n  text-transform: uppercase;\n  color: var(--htt-muted) !important;\n}\n\n.htt-insight-box p:last-child {\n  margin-bottom: 0;\n  color: var(--htt-text);\n}\n\n\n\/* Bibliography *\/\n\n.htt-bibliography {\n  margin: 3rem 0 0;\n}\n\n.htt-bibliography h2 {\n  margin-bottom: 1rem;\n}\n\n.htt-bibliography__grid {\n  display: grid;\n  grid-template-columns: repeat(2, minmax(0, 1fr));\n  gap: 1rem;\n}\n\n.htt-bibliography__card {\n  padding: 1.15rem 1.15rem 1.05rem;\n  border: 1px solid var(--htt-border);\n  border-radius: var(--htt-radius);\n  background: #fff;\n  box-shadow: var(--htt-shadow-soft);\n}\n\n.htt-bibliography__card h3 {\n  margin: 0 0 0.45rem;\n  font-size: 1rem;\n  line-height: 1.35;\n}\n\n.htt-bibliography__card p {\n  margin: 0 0 0.8rem;\n  font-size: 0.96rem;\n  line-height: 1.6;\n  color: var(--htt-text-soft);\n}\n\n.htt-bibliography__card a {\n  display: inline-flex;\n  align-items: center;\n  gap: 0.35rem;\n  font-size: 0.95rem;\n  font-weight: 600;\n  text-decoration: none;\n  border-bottom: 1px solid rgba(15, 23, 42, 0.18);\n  padding-bottom: 0.08rem;\n}\n\n.htt-bibliography__card a:hover,\n.htt-bibliography__card a:focus {\n  border-bottom-color: rgba(37, 99, 235, 0.45);\n}\n\n\/* Lists inside article *\/\n\n.htt-article ul,\n.htt-article ol {\n  margin: 0 0 1.2rem 1.2rem;\n  color: var(--htt-text-soft);\n}\n\n.htt-article li {\n  margin-bottom: 0.4rem;\n}\n\n\/* Spacing refinements *\/\n\n.htt-article > *:last-child,\n.htt-article__section > *:last-child,\n.htt-bibliography__card > *:last-child {\n  margin-bottom: 0;\n}\n\n\/* Responsive *\/\n\n@media (max-width: 900px) {\n  .htt-article {\n    font-size: 1rem;\n  }\n\n  .htt-bibliography__grid {\n    grid-template-columns: 1fr;\n  }\n}\n\n@media (max-width: 640px) {\n  .htt-article__toc,\n  .htt-definition-box,\n  .htt-insight-box,\n  .htt-bibliography__card,\n  .htt-faq details {\n    border-radius: 14px;\n  }\n\n  .htt-article__toc {\n    padding: 1.1rem 1rem 1rem;\n  }\n\n  .htt-definition-box,\n  .htt-insight-box {\n    padding: 1rem;\n  }\n\n  .htt-faq summary {\n    padding: 0.95rem 2.7rem 0.95rem 1rem;\n  }\n\n  .htt-faq details p {\n    padding: 0 1rem 1rem;\n  }\n\n  .htt-bibliography__card {\n    padding: 1rem;\n  }\n}\n\n\n.htt-article__quote-wrap {\n  margin: 1.7rem 0;\n}\n\n.htt-article__quote {\n  margin: 0;\n  padding: 1.2rem 1.25rem 1.2rem 1.35rem;\n  border-left: 4px solid #2563eb;\n  border-radius: 0 14px 14px 0;\n  background: #f8fafc;\n  font-size: 1.02rem;\n  line-height: 1.65;\n  font-weight: 600;\n  letter-spacing: -0.01em;\n  color: #0f172a;\n}\n\n.htt-article__quote-caption {\n  margin-top: 0.7rem;\n  margin-left: calc(4px + 1.35rem);\n  font-size: 0.95rem;\n  line-height: 1.5;\n  color: #64748b;\n}\n\n@media (max-width: 640px) {\n  .htt-article__quote {\n    padding: 1rem 1rem 1rem 1.1rem;\n    border-radius: 0 12px 12px 0;\n    font-size: 1rem;\n    line-height: 1.6;\n  }\n\n  .htt-article__quote-caption {\n    margin-top: 0.6rem;\n    margin-left: calc(4px + 1.1rem);\n    font-size: 0.9rem;\n  }\n}\n<\/style>\n\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"@id\": \"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/#faq\",\n  \"url\": \"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/\",\n  \"inLanguage\": \"en\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Does Anthropic\u2019s report say that AI is causing mass unemployment?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"No. At least for now, the report does not show a systematic increase in unemployment in the most exposed occupations. The most delicate signal instead concerns the slowdown in young people entering some high-exposure jobs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Which jobs are the most exposed according to Anthropic?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Among the most exposed roles are programmers, customer service representatives, data entry workers, medical documentation specialists, market analysts and financial profiles. More broadly, the activities most affected are cognitive, structured, digital and language-based ones.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What does observed exposure measure?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"It is a metric that combines the theoretical possibility that a language model can perform a task with real-world use observed in work contexts. It is meant to distinguish AI\u2019s technical potential from its concrete adoption at work.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Why can the risk for juniors be more important than the unemployment figure?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Because a market that stops hiring entry-level profiles may appear stable in the short term, but in the medium term it weakens the skills pipeline, reduces professional mobility and makes the training of future senior profiles more fragile.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Does high exposure to AI mean a job will disappear?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"No. Exposure is not destiny. Some roles will be compressed, others will be transformed, and others may still grow because AI increases their productivity or expands overall demand.\"\n      }\n    }\n  ]\n}\n<\/script>\n\n\n\n<!-- SECTION -->\n<section  class=\"block-banner-mmet darksection\" style=\"\">\n    <div class=\"htt-container htt-talk-idea\">\n        <div class=\"htt-talk-idea--left\">\n            <p>Want to discuss how AI adoption in your company can improve results and output quality?<\/p>\n        <\/div>\n        <div class=\"htt-talk-idea--right\">\n            <div class=\"htt-talk-idea--card\">\n                <h4>\ud83d\udc4b <br>Discuss it with                    Massimiliano!\n                <\/h4>\n                                        <div class=\"htt-talk-idea--person\">\n                            <div class=\"avatar\" style=\"background-image: url(https:\/\/www.htt.it\/wp-content\/uploads\/2023\/12\/avatar_massimiliano-1.webp)\"><\/div><p>Massimiliano Baldocchi<span>Massimiliano Baldocchi \u00e8 CEO di HT&amp;T Consulting e da oltre 30 anni opera nel settore della comunicazione, del marketing e del digitale. Laureato in Informatica presso l&#8217;Universit\u00e0 di Pisa, coordina la visione strategica dell&#8217;agenzia accompagnando aziende e brand nella definizione di strategie integrate tra dati, creativit\u00e0 e tecnologia.<\/span><\/p>                        <\/div>\n                                                    <!-- <a class=\"htt-talk-idea--meet\" href=\"https:\/\/www.htt.it\/contatti\/\">Prenota un meet<\/a> -->\n                <a class=\"htt-talk-idea--meet\" href=\"https:\/\/www.htt.it\/contatti\/\">Book a meeting<\/a>\n            <\/div>\n        <\/div>\n    <\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":20,"featured_media":7484,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1,120,122],"tags":[198,95,267,265,268,266],"class_list":["post-7491","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-agency","category-ai-en","category-future-insights-en","tag-ai-en","tag-intelligenza-artificiale-en","tag-automation","tag-future-of-work","tag-labor-market","tag-workforce-transformation"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Anthropic AI Study: Why Junior Jobs Are Most at Risk .<\/title>\n<meta name=\"description\" content=\"Anthropic\u2019s study shows AI won\u2019t replace all jobs, but junior roles are at risk, reshaping access to work and career growth.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Anthropic AI Study: Why Junior Jobs Are Most at Risk\" \/>\n<meta property=\"og:description\" content=\"Anthropic\u2019s study shows AI won\u2019t replace all jobs, but junior roles are at risk, reshaping access to work and career growth.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/\" \/>\n<meta property=\"og:site_name\" content=\"HT&amp;T Consulting\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/HttConsulting\" \/>\n<meta property=\"article:published_time\" content=\"2026-03-14T14:56:32+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-03-21T11:05:00+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ai-e-lavoro.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1044\" \/>\n\t<meta property=\"og:image:height\" content=\"1044\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Massimiliano Baldocchi\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@htt\" \/>\n<meta name=\"twitter:site\" content=\"@htt\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Massimiliano Baldocchi\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/\"},\"author\":{\"name\":\"Massimiliano Baldocchi\",\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/#\\\/schema\\\/person\\\/d097314406f9b8bb2bef7c594d83388c\"},\"headline\":\"Anthropic and AI in the workplace: young people at risk\",\"datePublished\":\"2026-03-14T14:56:32+00:00\",\"dateModified\":\"2026-03-21T11:05:00+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/\"},\"wordCount\":10,\"publisher\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.htt.it\\\/wp-content\\\/uploads\\\/2026\\\/03\\\/ai-e-lavoro.webp\",\"keywords\":[\"ai\",\"artificial intelligence\",\"automation\",\"Future of work\",\"Labor market\",\"Workforce transformation\"],\"articleSection\":[\"agency\",\"AI\",\"Future Insights\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/\",\"url\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/\",\"name\":\"Anthropic AI Study: Why Junior Jobs Are Most at Risk\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.htt.it\\\/wp-content\\\/uploads\\\/2026\\\/03\\\/ai-e-lavoro.webp\",\"datePublished\":\"2026-03-14T14:56:32+00:00\",\"dateModified\":\"2026-03-21T11:05:00+00:00\",\"description\":\"Anthropic\u2019s study shows AI won\u2019t replace all jobs, but junior roles are at risk, reshaping access to work and career growth.\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.htt.it\\\/wp-content\\\/uploads\\\/2026\\\/03\\\/ai-e-lavoro.webp\",\"contentUrl\":\"https:\\\/\\\/www.htt.it\\\/wp-content\\\/uploads\\\/2026\\\/03\\\/ai-e-lavoro.webp\",\"width\":1044,\"height\":1044,\"caption\":\"ai e lavoro, abbiamo sempre meno junior\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/anthropic-and-ai-in-the-workplace-young-people-at-risk\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.htt.it\\\/en\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Anthropic and AI in the workplace: young people at risk\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/#website\",\"url\":\"https:\\\/\\\/www.htt.it\\\/en\\\/\",\"name\":\"HT&T Consulting\",\"description\":\"Scale-up your digital business\",\"publisher\":{\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.htt.it\\\/en\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/www.htt.it\\\/en\\\/#\\\/schema\\\/person\\\/d097314406f9b8bb2bef7c594d83388c\",\"name\":\"Massimiliano Baldocchi\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/ee74c8fcce5556dd1c917b477e84c173a025529c0ebe30126a3a3857209ac3f7?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/ee74c8fcce5556dd1c917b477e84c173a025529c0ebe30126a3a3857209ac3f7?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/ee74c8fcce5556dd1c917b477e84c173a025529c0ebe30126a3a3857209ac3f7?s=96&d=mm&r=g\",\"caption\":\"Massimiliano Baldocchi\"},\"description\":\"Massimiliano Baldocchi \u00e8 CEO di HT&amp;T Consulting e da oltre 30 anni opera nel settore della comunicazione, del marketing e del digitale. Laureato in Informatica presso l'Universit\u00e0 di Pisa, coordina la visione strategica dell'agenzia accompagnando aziende e brand nella definizione di strategie integrate tra dati, creativit\u00e0 e tecnologia.\",\"sameAs\":[\"https:\\\/\\\/www.linkedin.com\\\/in\\\/massimilianobaldocchi\\\/\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Anthropic AI Study: Why Junior Jobs Are Most at Risk .","description":"Anthropic\u2019s study shows AI won\u2019t replace all jobs, but junior roles are at risk, reshaping access to work and career growth.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/","og_locale":"en_US","og_type":"article","og_title":"Anthropic AI Study: Why Junior Jobs Are Most at Risk","og_description":"Anthropic\u2019s study shows AI won\u2019t replace all jobs, but junior roles are at risk, reshaping access to work and career growth.","og_url":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/","og_site_name":"HT&amp;T Consulting","article_publisher":"https:\/\/www.facebook.com\/HttConsulting","article_published_time":"2026-03-14T14:56:32+00:00","article_modified_time":"2026-03-21T11:05:00+00:00","og_image":[{"width":1044,"height":1044,"url":"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ai-e-lavoro.webp","type":"image\/webp"}],"author":"Massimiliano Baldocchi","twitter_card":"summary_large_image","twitter_creator":"@htt","twitter_site":"@htt","twitter_misc":{"Written by":"Massimiliano Baldocchi","Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/#article","isPartOf":{"@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/"},"author":{"name":"Massimiliano Baldocchi","@id":"https:\/\/www.htt.it\/en\/#\/schema\/person\/d097314406f9b8bb2bef7c594d83388c"},"headline":"Anthropic and AI in the workplace: young people at risk","datePublished":"2026-03-14T14:56:32+00:00","dateModified":"2026-03-21T11:05:00+00:00","mainEntityOfPage":{"@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/"},"wordCount":10,"publisher":{"@id":"https:\/\/www.htt.it\/en\/#organization"},"image":{"@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/#primaryimage"},"thumbnailUrl":"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ai-e-lavoro.webp","keywords":["ai","artificial intelligence","automation","Future of work","Labor market","Workforce transformation"],"articleSection":["agency","AI","Future Insights"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/","url":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/","name":"Anthropic AI Study: Why Junior Jobs Are Most at Risk","isPartOf":{"@id":"https:\/\/www.htt.it\/en\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/#primaryimage"},"image":{"@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/#primaryimage"},"thumbnailUrl":"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ai-e-lavoro.webp","datePublished":"2026-03-14T14:56:32+00:00","dateModified":"2026-03-21T11:05:00+00:00","description":"Anthropic\u2019s study shows AI won\u2019t replace all jobs, but junior roles are at risk, reshaping access to work and career growth.","breadcrumb":{"@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/#primaryimage","url":"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ai-e-lavoro.webp","contentUrl":"https:\/\/www.htt.it\/wp-content\/uploads\/2026\/03\/ai-e-lavoro.webp","width":1044,"height":1044,"caption":"ai e lavoro, abbiamo sempre meno junior"},{"@type":"BreadcrumbList","@id":"https:\/\/www.htt.it\/en\/anthropic-and-ai-in-the-workplace-young-people-at-risk\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.htt.it\/en\/"},{"@type":"ListItem","position":2,"name":"Anthropic and AI in the workplace: young people at risk"}]},{"@type":"WebSite","@id":"https:\/\/www.htt.it\/en\/#website","url":"https:\/\/www.htt.it\/en\/","name":"HT&T Consulting","description":"Scale-up your digital business","publisher":{"@id":"https:\/\/www.htt.it\/en\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.htt.it\/en\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/www.htt.it\/en\/#\/schema\/person\/d097314406f9b8bb2bef7c594d83388c","name":"Massimiliano Baldocchi","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/ee74c8fcce5556dd1c917b477e84c173a025529c0ebe30126a3a3857209ac3f7?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/ee74c8fcce5556dd1c917b477e84c173a025529c0ebe30126a3a3857209ac3f7?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/ee74c8fcce5556dd1c917b477e84c173a025529c0ebe30126a3a3857209ac3f7?s=96&d=mm&r=g","caption":"Massimiliano Baldocchi"},"description":"Massimiliano Baldocchi \u00e8 CEO di HT&amp;T Consulting e da oltre 30 anni opera nel settore della comunicazione, del marketing e del digitale. Laureato in Informatica presso l'Universit\u00e0 di Pisa, coordina la visione strategica dell'agenzia accompagnando aziende e brand nella definizione di strategie integrate tra dati, creativit\u00e0 e tecnologia.","sameAs":["https:\/\/www.linkedin.com\/in\/massimilianobaldocchi\/"]}]}},"_links":{"self":[{"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/posts\/7491","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/comments?post=7491"}],"version-history":[{"count":3,"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/posts\/7491\/revisions"}],"predecessor-version":[{"id":7498,"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/posts\/7491\/revisions\/7498"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/media\/7484"}],"wp:attachment":[{"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/media?parent=7491"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/categories?post=7491"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.htt.it\/en\/wp-json\/wp\/v2\/tags?post=7491"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}