{"id":7224,"date":"2026-05-06T22:52:18","date_gmt":"2026-05-06T14:52:18","guid":{"rendered":"https:\/\/moresourcing.com\/calibrate-ai-use-to-the-decision-at-hand\/"},"modified":"2026-05-06T22:52:18","modified_gmt":"2026-05-06T14:52:18","slug":"calibrate-ai-use-to-the-decision-at-hand","status":"publish","type":"post","link":"https:\/\/moresourcing.com\/zh\/calibrate-ai-use-to-the-decision-at-hand\/","title":{"rendered":"Calibrate AI Use to the Decision at Hand"},"content":{"rendered":"<p><\/p>\n<div id=\"article-content\">\n<header class=\"article-header\">\n    <a href=\"https:\/\/sloanreview.mit.edu\/frontiers\/\" class=\"article-header__content-meta\"><span>\u524d\u6cbf<\/span><\/a>     <\/p>\n<h2 class=\"article-header__deck\">Some decisions are narrow and \ufeffcan be modeled\ufeff; others are wide and require stakeholder alignment. Understand this distinction to use the type of AI that will be most helpful.&#13;<br \/>\n<\/h2>\n<div class=\"article-header__info\">\n            <a href=\"#article-authors\" class=\"article-header__byline\">Pedro Amorim, Amr Saleh, and Ulrika Cederskog Sundling<\/a><br \/>\n            <time class=\"article-header__date pub-date-dimension\" datetime=\"2026-05-06T07:00:43-04:00\" pubdate=\"\"><br \/>\n                <abbr class=\"published updated\" title=\"2026-05-06T07:00:43-04:00\">May 06, 2026<\/abbr><br \/>\n            <\/time><br \/>\n            <span class=\"article-header__reading-time\">Reading Time: 9 min\u00a0<\/span>\n        <\/div>\n<\/header>\n<div class=\"standard-content article-content\">\n<div class=\"article-left-col\">\n<section class=\"article-topics\">\n<h4 class=\"article-topics__title\">\u4e3b\u9898<\/h4>\n<\/section>\n<section class=\"article-section\">\n<h4 class=\"article-section__title\">\u524d\u6cbf<\/h4>\n<p>\n            \u4e00\u4e2a <cite>\u9ebb\u7701\u7406\u5de5\u5b66\u9662 SMR<\/cite> \u63a2\u7d22\u6280\u672f\u5982\u4f55\u91cd\u5851\u7ba1\u7406\u5b9e\u8df5\u7684\u5021\u8bae\u3002        <\/p>\n<p>        <a href=\"https:\/\/sloanreview.mit.edu\/big-ideas\/frontiers\/\" class=\"article-section__link\"><\/p>\n<p>           \u672c\u7cfb\u5217\u4e2d\u7684\u66f4\u591a\u5185\u5bb9<br \/>\n                      <\/a><\/p>\n<\/section><\/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\" decoding=\"async\" width=\"1290\" height=\"860\" alt=\"\" class=\"wp-image-126950\" srcset=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/05\/Calibrate-AI-Use-to-the-Decision-at-Hand.jpg 1290w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-300x200.jpg 300w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-150x100.jpg 150w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-768x512.jpg 768w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-764x509.jpg 764w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-382x255.jpg 382w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-870x580.jpg 870w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-435x290.jpg 435w\" data-lazy-sizes=\"(max-width: 1290px) 100vw, 1290px\" src=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/05\/Calibrate-AI-Use-to-the-Decision-at-Hand.jpg\"\/><img fetchpriority=\"high\" decoding=\"async\" width=\"1290\" height=\"860\" src=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/05\/Calibrate-AI-Use-to-the-Decision-at-Hand.jpg\" alt=\"\" class=\"wp-image-126950\" srcset=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/05\/Calibrate-AI-Use-to-the-Decision-at-Hand.jpg 1290w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-300x200.jpg 300w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-150x100.jpg 150w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-768x512.jpg 768w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-764x509.jpg 764w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-382x255.jpg 382w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-870x580.jpg 870w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/04\/2026SUMMER_Amorim-1290x860-1-435x290.jpg 435w\" sizes=\"(max-width: 1290px) 100vw, 1290px\"\/><figcaption>\n<p class=\"attribution\">PPaint\/Ikon Images<\/p>\n<\/figcaption><\/figure>\n<div class=\"article-summary\"><strong class=\"article-summary__strong\">\u6458\u8981 <\/strong><\/p>\n<p>Leaders should understand the differing capabilities of different flavors of AI when applying the tools to decision-making. Analytical AI, such as traditional machine learning models, are useful for optimization problems that require a predictive recommendation. Generative AI is better applied around the decision-making process, where it can help users explore and understand a less-precise problem.<\/p>\n<\/div>\n<div class=\"article-narration\">\n<p>    <a href=\"#narration\" id=\"narrationModal\" class=\"j-audio-trigger current-speed\" title=\"Calibrate AI Use to the Decision at Hand\"><br \/>\n        <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"50\" height=\"50\" viewbox=\"0 0 50 50\" fill=\"none\">\n            <g clip-path=\"url(#clip0_2534_8292)\">\n            <g clip-path=\"url(#clip1_2534_8292)\">\n            <path d=\"M25 50C38.8071 50 50 38.8071 50 25C50 11.1929 38.8071 0 25 0C11.1929 0 0 11.1929 0 25C0 38.8071 11.1929 50 25 50Z\" fill=\"#005B9C\"\/>\n            <path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M19.985 25.0001V17.0708C19.985 16.5579 20.6336 16.2585 21.1033 16.5547L27.245 20.4252L33.6852 24.4837C34.0849 24.7358 34.0849 25.2645 33.6852 25.5166L27.245 29.5753L21.1033 33.4458C20.6336 33.7418 19.985 33.4423 19.985 32.9294V25.0001Z\" fill=\"white\"\/>\n            <\/g>\n            <\/g>\n            <defs>\n            <clippath id=\"clip0_2534_8292\">\n            <rect width=\"50\" height=\"50\" fill=\"white\"\/>\n            <\/clippath>\n            <clippath id=\"clip1_2534_8292\">\n            <rect width=\"50\" height=\"50\" fill=\"white\"\/>\n            <\/clippath>\n            <\/defs>\n        <\/svg><br \/>\n        <span>Listen to \u201cCalibrate AI Use to the Decision at Hand\u201d <span>(14:33)<\/span><\/span><br \/>\n    <\/a>\n<\/div>\n<p><span class=\"smr-leadin\">On a rainy Tuesday in London,<\/span> the leadership team of a consumer goods company reviewed two business decisions: \u201cWhere should we open our next five stores?\u201d and \u201cShould we pivot the brand toward wellness?\u201d Generative AI had been used to support the decision-making process for addressing both questions. The team ended up with plenty of plausible qualitative arguments for the proposed road map for store expansion \u2014 without data or analytics to support these recommendations. The tool had helped the team produce a polished narrative on the wellness pivot, along with a compelling deck advocating the strategic move, but stakeholder engagement was shallow, and there wasn\u2019t a shared conviction that the organization was ready to move.<\/p>\n<p>The meeting exposed the flawed assumption that all AI is the same and that every type of artificial intelligence supports decision-making equally. In reality, different decisions require fundamentally different AI roles. Some decisions are narrow: Objectives are clear, data is available, and outcomes can be measured quickly. Others are wide: Goals are contested, information is incomplete, and alignment matters as much as analysis. When leaders treat both decision types as the same, they predictably misapply AI technology, using generative tools where analytical engines are needed or where the real work is deliberation and commitment. The result is a disappointing output that fails to support narrow decisions and fragile buy-in and difficult execution for wide decisions that demand socialization and alignment.<\/p>\n<p>That mismatch is showing up across industries. AI adoption is now widespread, yet many organizations still struggle to convert AI activity into measurable business impact. In its <a href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-insights\/the-state-of-ai\" target=\"_blank\">2025 report on the state of AI<\/a>, McKinsey describes this gap starkly: 88% of companies now use AI in at least one function, but only around 40% are able to see a positive impact on the bottom line. In our work with executive teams, the pattern behind that gap is consistent. The pressure to use AI \u2014 amplified by headlines about generative and agentic systems \u2014 often outruns the harder discipline of deciding where AI should lead, where it should support, and what kind of AI fits the decision at hand. As a result, teams build impressive decks for problems that require more time for internal alignment, and they use conversational generative tools for decisions that demand rigorous analytics.<\/p>\n<p>The solution is to calibrate AI\u2019s role in the decision.<\/p>\n<div class=\"article-left-col--footer\">\n<section class=\"article-topics\">\n<h4 class=\"article-topics__title\">\u4e3b\u9898<\/h4>\n<\/section>\n<section class=\"article-section\">\n<h4 class=\"article-section__title\">\u524d\u6cbf<\/h4>\n<p>\n            \u4e00\u4e2a <cite>\u9ebb\u7701\u7406\u5de5\u5b66\u9662 SMR<\/cite> \u63a2\u7d22\u6280\u672f\u5982\u4f55\u91cd\u5851\u7ba1\u7406\u5b9e\u8df5\u7684\u5021\u8bae\u3002        <\/p>\n<p>        <a href=\"https:\/\/sloanreview.mit.edu\/big-ideas\/frontiers\/\" class=\"article-section__link\"><\/p>\n<p>           \u672c\u7cfb\u5217\u4e2d\u7684\u66f4\u591a\u5185\u5bb9<br \/>\n                      <\/a><\/p>\n<\/section><\/div>\n<div class=\"article-authors\" id=\"article-authors\">\n<h4 class=\"article-authors__title\">\u5173\u4e8e\u4f5c\u8005<\/h4>\n<div class=\"article-authors__bio\">\n<p>Pedro Amorim is a professor at the University of Porto and cofounder of LTPlabs. Amr Saleh is a generative AI and optimization consultant at LTPlabs. Ulrika Cederskog Sundling is an investor, a board director, and a member of LTPlabs\u2019s advisory board.<\/p>\n<\/div><\/div>\n<\/div><\/div>\n<p>#Calibrate #Decision #Hand<\/p>","protected":false},"excerpt":{"rendered":"<p>Frontiers Some decisions are narrow and \ufeffcan be modeled\ufeff; others are wide and require stakeholder alignment. Understand this distinction to use the type of AI that will be most helpful.&#13; Pedro Amorim, Amr Saleh, and Ulrika Cederskog Sundling May 06, 2026 Reading Time: 9 min\u00a0 Topics Frontiers An MIT SMR initiative exploring how technology is [&hellip;]<\/p>","protected":false},"author":1,"featured_media":7225,"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-7224","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>Calibrate AI Use to the Decision at Hand - 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\/zh\/calibrate-ai-use-to-the-decision-at-hand\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Calibrate AI Use to the Decision at Hand\" \/>\n<meta property=\"og:description\" content=\"Frontiers Some decisions are narrow and \ufeffcan be modeled\ufeff; others are wide and require stakeholder alignment. 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