{"id":8652,"date":"2026-07-24T10:20:34","date_gmt":"2026-07-24T02:20:34","guid":{"rendered":"https:\/\/moresourcing.com\/research-why-some-junior-employees-work-well-with-ai-and-others-dont\/"},"modified":"2026-07-24T10:20:34","modified_gmt":"2026-07-24T02:20:34","slug":"research-why-some-junior-employees-work-well-with-ai-and-others-dont","status":"publish","type":"post","link":"https:\/\/moresourcing.com\/en\/research-why-some-junior-employees-work-well-with-ai-and-others-dont\/","title":{"rendered":"Why Some Junior Employees Work Well with AI\u2014and Others Don\u2019t"},"content":{"rendered":"<p><\/p>\n<div>\n<p class=\"Paragraph-module-scss-module__UwInRW__text\" data-first-paragraph=\"true\">Entry-level employees are on the front lines of a rapid shift in knowledge work. These jobs used to be full of tasks that created an onramp into an industry and helped junior employees start building expertise. But now, many of these tasks are <a href=\"http:\/\/hbr.org\/podcast\/2026\/04\/strategy-summit-2026-whos-going-to-succeed-with-ai\" class=\"ContentLink-module-scss-module__qKDjGa__anchor\">at risk of being delegated<\/a> to AI-powered workflows, which are increasingly capable of handling analytical, information-intensive assignments. And as AI continues to improve, research has shown it is quickly <a href=\"https:\/\/www.hbs.edu\/faculty\/Pages\/item.aspx?num=67197\" class=\"ContentLink-module-scss-module__qKDjGa__anchor\">resetting<\/a> the <a href=\"https:\/\/www.researchgate.net\/publication\/382782110_The_Crowdless_Future_How_Generative_AI_Is_Shaping_the_Future_of_Human_Crowdsourcing\" class=\"ContentLink-module-scss-module__qKDjGa__anchor\">baseline<\/a>, with the standard for acceptable output rising as models improve.<\/p>\n<\/div>\n<p><script async=\"\" defer=\"\" crossorigin=\"anonymous\" src=\"https:\/\/connect.facebook.net\/en_US\/sdk.js#version=v19.2&amp;appId=1761258887507575&amp;xfbml=false&amp;status=true\"><\/script><\/p>\n<p>#Junior #Employees #Work #AIand #Dont<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Entry-level employees are on the front lines of a rapid shift in knowledge work. These jobs used to be full of tasks that created an onramp into an industry and helped junior employees start building expertise. But now, many of these tasks are at risk of being delegated to AI-powered workflows, which are increasingly capable [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":8653,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[9],"tags":[],"class_list":["post-8652","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-management"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.7.1 (Yoast SEO v25.8) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Why Some Junior Employees Work Well with AI\u2014and Others Don\u2019t - MORE SOURCING LTD<\/title>\n<meta name=\"description\" content=\"Organizations need to understand how individuals create value beyond the AI baseline in real organizational settings, particularly in higher-stakes professional work requiring judgment, domain expertise, and decision-ready outputs. KPMG and researchers from the University of Texas conducted a large-scale field study with 523 early-career professionals where participants completed business-specific tasks using an AI agent built for the domain. This research can help answer two questions: 1) What enables early career employees to add value in AI\u2011enabled workflows? And 2) how can those capabilities be intentionally developed in ways that sustain continuous improvement as AI continues to advance? The findings sorted participants into three groups: AI apprentices, AI delegators, and AI amplifiers. A surprise in the findings was that foundational skills such as critical thinking abilities, AI literacy, and domain knowledge weren\u2019t clear signals for who fell into which group. This can help leaders rethink how to design entry-level work and how to hire for these jobs.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/moresourcing.com\/en\/research-why-some-junior-employees-work-well-with-ai-and-others-dont\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Why Some Junior Employees Work Well with AI\u2014and Others Don\u2019t\" \/>\n<meta property=\"og:description\" content=\"Organizations need to understand how individuals create value beyond the AI baseline in real organizational settings, particularly in higher-stakes professional work requiring judgment, domain expertise, and decision-ready outputs. KPMG and researchers from the University of Texas conducted a large-scale field study with 523 early-career professionals where participants completed business-specific tasks using an AI agent built for the domain. This research can help answer two questions: 1) What enables early career employees to add value in AI\u2011enabled workflows? And 2) how can those capabilities be intentionally developed in ways that sustain continuous improvement as AI continues to advance? The findings sorted participants into three groups: AI apprentices, AI delegators, and AI amplifiers. A surprise in the findings was that foundational skills such as critical thinking abilities, AI literacy, and domain knowledge weren\u2019t clear signals for who fell into which group. 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