{"id":8341,"date":"2026-07-08T21:15:40","date_gmt":"2026-07-08T13:15:40","guid":{"rendered":"https:\/\/moresourcing.com\/genai-success-metrics-look-beyond-reduced-workload\/"},"modified":"2026-07-08T21:15:40","modified_gmt":"2026-07-08T13:15:40","slug":"genai-success-metrics-look-beyond-reduced-workload","status":"publish","type":"post","link":"https:\/\/moresourcing.com\/en\/genai-success-metrics-look-beyond-reduced-workload\/","title":{"rendered":"GenAI Success Metrics: Look Beyond Reduced Workload"},"content":{"rendered":"<p><\/p>\n<div>\n<aside class=\"article-ad ad-300  ad-300x250 ad-desktop\">\n<\/aside>\n<aside class=\"article-ad ad-300  ad-300x250 ad-mobile\">\n<\/aside>\n<figure class=\"article-inline\">\n<img fetchpriority=\"high\" fetchpriority=\"high\" decoding=\"async\" width=\"1290\" height=\"860\" alt=\"\" class=\"wp-image-127942\" srcset=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/07\/GenAI-Success-Metrics-Look-Beyond-Reduced-Workload.jpg 1290w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-300x200.jpg 300w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-150x100.jpg 150w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-768x512.jpg 768w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-764x509.jpg 764w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-382x255.jpg 382w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-870x580.jpg 870w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-435x290.jpg 435w\" data-lazy-sizes=\"(max-width: 1290px) 100vw, 1290px\" src=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/07\/GenAI-Success-Metrics-Look-Beyond-Reduced-Workload.jpg\"\/><img fetchpriority=\"high\" fetchpriority=\"high\" decoding=\"async\" width=\"1290\" height=\"860\" src=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/07\/GenAI-Success-Metrics-Look-Beyond-Reduced-Workload.jpg\" alt=\"\" class=\"wp-image-127942\" srcset=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/07\/GenAI-Success-Metrics-Look-Beyond-Reduced-Workload.jpg 1290w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-300x200.jpg 300w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-150x100.jpg 150w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-768x512.jpg 768w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-764x509.jpg 764w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-382x255.jpg 382w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-870x580.jpg 870w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/06\/Shah-1290x860-1-435x290.jpg 435w\" sizes=\"(max-width: 1290px) 100vw, 1290px\"\/><figcaption>\n<p class=\"attribution\">Matt Harrison Clough \/ Ikon Images<\/p>\n<\/figcaption><\/figure>\n<div class=\"article-summary\"><strong class=\"article-summary__strong\">Summary: <\/strong><\/p>\n<p>At the Community College of Philadelphia, generative AI tools didn\u2019t magically free up people\u2019s time or supercharge one productivity metric across the board. An analysis found that GenAI resulted in different workflow gains for key roles: decisiveness for executives, speed for operational leaders, and resolution efficiency for student-facing professionals. When judging GenAI\u2019s success, examine how your organization\u2019s work changed shape.<\/p>\n<\/div>\n<aside class=\"callout-info\">\n<h4>The Research<\/h4>\n<p>The authors performed a four-year, fixed-window observational analysis of administrative work inside a large U.S. public higher-education institution. Generative AI tools were introduced to executive leaders, operational leaders, and student-facing professionals throughout the organization in 2026. Staffing levels and work hours remained stable across the period studied. The analysis focused on work composition, decision quality, and coordination patterns rather than task speed or automation rates.<\/p>\n<\/aside>\n<p><span class=\"smr-leadin\">When leaders talk<\/span> about generative AI tools, one promise comes up repeatedly: These tools will save time.<\/p>\n<p>Fewer emails. Fewer meetings. Less administrative drag.<\/p>\n<p>That expectation shapes how many organizations decide whether GenAI is \u201cworking\u201d \u2014 and why they\u2019re often disappointed when people\u2019s calendars don\u2019t suddenly open up.<\/p>\n<p>But for our organization, time savings turned out to be the wrong place to look.<\/p>\n<p>What we saw inside a large public higher-education institution, the Community College of Philadelphia, wasn\u2019t less work, but work that <em>changed form<\/em>. When generative AI entered our organization\u2019s everyday workflows in 2026, coordination didn\u2019t vanish. It shifted away from meetings and toward writing, away from clarification and toward clearer first passes, away from back-and-forth deliberation and toward faster closure on decisions.<\/p>\n<p>To understand what really changed, we looked at how three of the professional roles within one administrative unit \u2014 executive leaders, operational leaders, and student-facing professionals \u2014 worked during the same six-week period across four different years. What emerged wasn\u2019t a story about automation replacing people. It was a story about how work gets shaped, completed, and passed along.<\/p>\n<p>That distinction matters. Organizations that judge AI only by hours saved risk missing the real gains and feeling underwhelmed by AI, even when it\u2019s quietly doing what it\u2019s supposed to do.<\/p>\n<h3>Three Groups\u2019 GenAI Gains<\/h3>\n<p>GenAI tools showed up in day-to-day work at our college in 2026. To understand the impact GenAI had on the three groups of professionals, we examined the same six-week window each year (February\u202f1 through March\u202f15), comparing work in 2026 with patterns from the previous three years.<\/p>\n<p>We didn\u2019t ask, \u201cHow fast did people work?\u201d<\/p>\n<p>We asked, \u201cWhat kind of work were they producing?\u201d<\/p>\n<p>Because staffing levels and work hours remained essentially the same across all four years, any differences we observed reflected changes in how work was done, not changes in capacity. <\/p>\n<div class=\"article-authors\" id=\"article-authors\">\n<h4 class=\"article-authors__title\">About the Authors<\/h4>\n<div class=\"article-authors__bio\">\n<p>Vishal Shah is dean of the Division of Math, Science, and Health Careers at the Community College of Philadelphia. Andrenna Gibson is an operational leader at the Community College of Philadelphia, responsible for translating executive decisions into day-to-day processes that support students, faculty, and staff. Tanika Teagle leads student-facing admissions processes for select health care programs at the Community College of Philadelphia.<\/p>\n<\/div><\/div>\n<div class=\"article-doi\">\n    <a href=\"https:\/\/doi.org\/10.63383\/dFKS6287\" target=\"_blank\" class=\"article-doi__number\">https:\/\/doi.org\/10.63383\/dFKS6287<\/a>\n<\/div>\n<\/div>\n<p>#GenAI #Success #Metrics #Reduced #Workload<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Matt Harrison Clough \/ Ikon Images Summary: At the Community College of Philadelphia, generative AI tools didn\u2019t magically free up people\u2019s time or supercharge one productivity metric across the board. An analysis found that GenAI resulted in different workflow gains for key roles: decisiveness for executives, speed for operational leaders, and resolution efficiency for student-facing [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":8342,"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-8341","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>GenAI Success Metrics: Look Beyond Reduced Workload - MORE SOURCING LTD<\/title>\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\/genai-success-metrics-look-beyond-reduced-workload\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"GenAI Success Metrics: Look Beyond Reduced Workload\" \/>\n<meta property=\"og:description\" content=\"Matt Harrison Clough \/ Ikon Images Summary: At the Community College of Philadelphia, generative AI tools didn\u2019t magically free up people\u2019s time or supercharge one productivity metric across the board. 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