{"id":3719194,"date":"2026-05-08T16:12:46","date_gmt":"2026-05-08T20:12:46","guid":{"rendered":"https:\/\/www.pymnts.com\/?p=3719194"},"modified":"2026-05-08T16:12:46","modified_gmt":"2026-05-08T20:12:46","slug":"anthropic-found-ai-makes-impractical-work-worth-doing","status":"publish","type":"post","link":"https:\/\/www.pymnts.com\/artificial-intelligence-2\/2026\/anthropic-found-ai-makes-impractical-work-worth-doing\/","title":{"rendered":"Anthropic Found AI Makes Impractical Work Worth Doing"},"content":{"rendered":"<p>The productivity debate around enterprise artificial intelligence (AI) has narrowed to one question: how much faster can workers complete existing tasks? <a href=\"https:\/\/www.anthropic.com\/\">Anthropic<\/a>\u2019s internal research suggests that framing leaves something out. The company <a href=\"https:\/\/www.anthropic.com\/research\/how-ai-is-transforming-work-at-anthropic\">found<\/a> that 27% of AI-assisted work inside Anthropic came from tasks employees wouldn\u2019t have attempted without AI. That work wasn\u2019t impractical because it lacked value. The time cost made it impractical.<\/p><div\r\n\tid=\"article-paywall-overlay\"\r\n\tclass=\"d-none\"\r\n>\r\n\t<div id=\"article-paywall-content\" class=\"my-4\">\r\n\t\t\n<div class=\"wpcf7 no-js\" id=\"wpcf7-f2699550-o1\" lang=\"en-US\" dir=\"ltr\" data-wpcf7-id=\"2699550\">\n<div class=\"screen-reader-response\"><p role=\"status\" aria-live=\"polite\" aria-atomic=\"true\"><\/p> <ul><\/ul><\/div>\n<form action=\"\/wp-json\/wp\/v2\/posts\/3719194#wpcf7-f2699550-o1\" method=\"post\" class=\"wpcf7-form init pymnts-article-paywall-form\" aria-label=\"Contact form\" novalidate=\"novalidate\" data-status=\"init\">\n<fieldset class=\"hidden-fields-container\"><input type=\"hidden\" name=\"_wpcf7\" value=\"2699550\" \/><input type=\"hidden\" name=\"_wpcf7_version\" value=\"6.1.5\" \/><input type=\"hidden\" name=\"_wpcf7_locale\" value=\"en_US\" \/><input type=\"hidden\" name=\"_wpcf7_unit_tag\" value=\"wpcf7-f2699550-o1\" \/><input type=\"hidden\" name=\"_wpcf7_container_post\" value=\"0\" 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you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our <a class=\"fw-bold\" href=\"https:\/\/pymnts-com-develop.go-vip.net\/privacy-policy\/\">Privacy Policy<\/a> and <a class=\"fw-bold\" href=\"https:\/\/pymnts-com-develop.go-vip.net\/terms-conditions\/\">Terms and Conditions<\/a>.\n\t\t\t\t<\/p>\n\t\t\t\t<p><input id='hiddenPath' type='hidden' name='path' value='' \/><input type='hidden' name='userDeviceId' id='userDeviceId' \/><input type='hidden' name='pageTitle' id='pageTitle' \/>\n\t\t\t\t<\/p>\n\t\t\t<\/div>\n\t\t\t<div class=\"col-12\">\n\t\t\t\t<div id='formButtonRow' class='container mt-1 px-0'>\n\t\t\t\t\t<p><input class=\"wpcf7-form-control wpcf7-submit has-spinner btn btn-dark text-uppercase py-2 px-5 small\" id=\"theSubmitButton\" type=\"submit\" value=\"Submit\" \/>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/div><input type=\"hidden\" name=\"post_id\" value=\"3719194\" \/><input type=\"hidden\" name=\"source\" value=\"https:\/\/www.pymnts.com\/artificial-intelligence-2\/2026\/anthropic-found-ai-makes-impractical-work-worth-doing\/\" \/><p style=\"display: none !important;\" class=\"akismet-fields-container\" data-prefix=\"_wpcf7_ak_\"><label>&#916;<textarea name=\"_wpcf7_ak_hp_textarea\" cols=\"45\" rows=\"8\" maxlength=\"100\"><\/textarea><\/label><input type=\"hidden\" id=\"ak_js_1\" name=\"_wpcf7_ak_js\" value=\"75\"\/><script>document.getElementById( \"ak_js_1\" ).setAttribute( \"value\", ( new Date() ).getTime() );<\/script><\/p><div class=\"wpcf7-response-output\" aria-hidden=\"true\"><\/div>\n<\/form>\n<\/div>\n\r\n\t<\/div>\r\n<\/div>\r\n<div id=\"article-paywall-hidden-content\">\r\n\t\n<h2><strong>What the Data Showed<\/strong><\/h2>\n<p>Anthropic <a href=\"https:\/\/www.anthropic.com\/research\/how-ai-is-transforming-work-at-anthropic\">surveyed<\/a> engineers and researchers across the organization, conducted 53 in-depth interviews and analyzed 200,000 internal Claude Code transcripts. Employees reported using Claude in 60% of their work and estimated productivity gains averaging around 50%, up from 20% the prior year. Usage rose from 28% of daily work to 60% over the same period.<\/p>\n<p>The output data is more concrete. Across nearly every task category, employees reported slightly less time spent per task but substantially more output volume. Claude Code usage shifted toward more complex work: the average number of consecutive tool calls the model completed without human input doubled from roughly 10 to 21, and the share of tasks involving new feature implementation grew from 14% to 37%.<\/p>\n<p>Engineers described using AI to build interactive dashboards, scale deprioritized projects, fix long-neglected code quality issues and run exploratory research that wouldn\u2019t have justified the time cost manually. One researcher described running multiple Claude instances in parallel to test different approaches simultaneously, treating the model less like a faster car and more like a fleet.<\/p>\n<p><a href=\"https:\/\/openai.com\/\">OpenAI<\/a>\u2019s enterprise research <a href=\"https:\/\/openai.com\/index\/the-state-of-enterprise-ai-2025-report\/\">found<\/a> a similar pattern, with 75% of surveyed workers reporting they could complete new tasks they previously couldn\u2019t perform. EY\u2019s US AI Pulse Survey <a href=\"https:\/\/www.ey.com\/en_us\/newsroom\/2025\/12\/ai-driven-productivity-is-fueling-reinvestment-over-workforce-reductions\">found<\/a> that 39% of organizations were reinvesting AI-driven productivity gains into research and development, suggesting the expansion effect extends beyond individual task completion.<\/p>\n<h2><strong>Where Enterprises Are Struggling<\/strong><\/h2>\n<p>The broader enterprise picture is less uniform. PYMNTS Intelligence <a href=\"https:\/\/www.pymnts.com\/artificial-intelligence-2\/2026\/rising-ai-adoption-is-driving-up-enterprise-costs\/\">found<\/a> that 71% of executives at companies with at least $1 billion in annual revenue identified organizational readiness as the primary limit on AI performance. Only 11% said the technology itself was the barrier. PYMNTS Intelligence <a href=\"https:\/\/www.pymnts.com\/study_posts\/no-roadmap-no-problem-how-enterprises-are-reinventing-the-ai-workforce\/\">reported<\/a> that 58% of CFOs named talent shortages as a leading challenge, rising to 71% among services firms.<\/p><div id=\"pymnt-4267521000\" class=\"pymnt-content pymnt-entity-placement\" style=\"margin-top: 50px;\"><p style=\"text-align:center\">Advertisement: Scroll to Continue<\/p><script async type=\"text\/javascript\" id=\"dianomi_context_script\" src=\"https:\/\/www.dianomi.com\/js\/contextfeed.js\"><\/script> \r\n<div class=\"dianomi_context\" data-dianomi-context-id=\"4329\"><\/div><\/div>\n<p>Cost control is a parallel pressure. PYMNTS <a href=\"https:\/\/www.pymnts.com\/artificial-intelligence-2\/2026\/rising-ai-adoption-is-driving-up-enterprise-costs\/\">reported<\/a> that Uber\u2019s AI budget surged past projections as internal use of Claude Code scaled, with roughly 11% of live updates to its back-end systems now written by AI agents and research and development expenses rising 9% to $3.4 billion in 2025.<\/p>\n<h2><strong>The Economics of Execution<\/strong><\/h2>\n<p>When AI reduces the cost of analysis, documentation, coding and research, work that once sat below the viability threshold moves above it. Deloitte <a href=\"https:\/\/www.deloitte.com\/us\/en\/what-we-do\/capabilities\/applied-artificial-intelligence\/content\/state-of-ai-in-the-enterprise.html\">found<\/a> that only 34% of enterprises are using AI to deeply transform core processes and products, while the remaining two-thirds are capturing efficiency gains without redesigning underlying operations.<\/p>\n<p>The internal findings carry limits. Anthropic engineers have early access to frontier models, work in a stable field and are themselves building the technology. The company acknowledged the findings don\u2019t generalize directly to other organizations. PYMNTS Intelligence <a href=\"https:\/\/www.pymnts.com\/news\/artificial-intelligence\/2026\/34-percent-of-cfos-say-productivity-is-the-top-reason-for-ai-adoption\/\">found<\/a> that 34% of CFOs at large companies cited productivity as the top reason for AI adoption. Anthropic plans to expand the research beyond engineers to understand how AI affects roles across the organization, with further findings expected in 2026.<\/p>\n\r\n<\/div>\r\n<script>\r\n\twindow.pymntsAllowedArticleCount = 1;\r\n\twindow.pymntsPostID = 3719194;\r\n<\/script>","protected":false},"excerpt":{"rendered":"<p>The productivity debate around enterprise artificial intelligence (AI) has narrowed to one question: how much faster can workers complete existing tasks? Anthropic\u2019s internal research suggests that framing leaves something out. The company found that 27% of AI-assisted work inside Anthropic came from tasks employees wouldn\u2019t have attempted without AI. That work wasn\u2019t impractical because it [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":3719277,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","pymnts_footnotes":""},"categories":[65579],"tags":[9498,76295,9181,19817,9206,133069],"class_list":["post-3719194","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence-2","tag-ai","tag-anthropic","tag-automation","tag-digital-transformation","tag-news","tag-pymnts-news"],"acf":{"suggested_titles":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.2 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Anthropic Found AI Makes Impractical Work Worth Doing<\/title>\n<meta name=\"description\" content=\"Enterprises bet AI would accelerate existing work. 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