{"id":8873,"date":"2026-08-05T23:11:09","date_gmt":"2026-08-05T15:11:09","guid":{"rendered":"https:\/\/moresourcing.com\/stop-prompting-ai-start-directing-it\/"},"modified":"2026-08-05T23:11:09","modified_gmt":"2026-08-05T15:11:09","slug":"stop-prompting-ai-start-directing-it","status":"publish","type":"post","link":"https:\/\/moresourcing.com\/ja\/stop-prompting-ai-start-directing-it\/","title":{"rendered":"Stop Prompting AI. Start Directing It"},"content":{"rendered":"<p><\/p>\n<div id=\"article-content\">\n<header class=\"article-header\">\n    <a href=\"https:\/\/sloanreview.mit.edu\/?content_type=research-feature\" class=\"article-header__content-meta\"><span>\u7814\u7a76\u7279\u96c6<\/span><\/a>     <\/p>\n<h2 class=\"article-header__deck\">Conversational AI speeds up familiar work. Configuring AI to interrogate your data \u2014 what the authors call <em>directing intelligence<\/em> \u2014 surfaces insights that familiar ways of working tend to miss.&#13;<br \/>\n<\/h2>\n<div class=\"article-header__info\">\n            <a href=\"#article-authors\" class=\"article-header__byline\">Jennifer Sloan and Vern L. Glaser<\/a><br \/>\n            <time class=\"article-header__date pub-date-dimension\" datetime=\"2026-08-05T07:00:54-04:00\" pubdate=\"\"><br \/>\n                <abbr class=\"published updated\" title=\"2026-08-05T07:00:54-04:00\">August 05, 2026<\/abbr><br \/>\n            <\/time><br \/>\n            <span class=\"article-header__reading-time\">\u8aad\u66f8\u6642\u9593: 19 \u5206\u00a0<\/span>\n        <\/div>\n<\/header>\n<div class=\"standard-content article-content\">\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-128377\" srcset=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/08\/Stop-Prompting-AI-Start-Directing-It.jpg 1290w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-300x200.jpg 300w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-150x100.jpg 150w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-768x512.jpg 768w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-764x509.jpg 764w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-382x255.jpg 382w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-870x580.jpg 870w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-435x290.jpg 435w\" data-lazy-sizes=\"(max-width: 1290px) 100vw, 1290px\" src=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/08\/Stop-Prompting-AI-Start-Directing-It.jpg\"\/><img fetchpriority=\"high\" decoding=\"async\" width=\"1290\" height=\"860\" src=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/08\/Stop-Prompting-AI-Start-Directing-It.jpg\" alt=\"\" class=\"wp-image-128377\" srcset=\"https:\/\/moresourcing.com\/wp-content\/uploads\/2026\/08\/Stop-Prompting-AI-Start-Directing-It.jpg 1290w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-300x200.jpg 300w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-150x100.jpg 150w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-768x512.jpg 768w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-764x509.jpg 764w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-382x255.jpg 382w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-870x580.jpg 870w, https:\/\/sloanreview.mit.edu\/wp-content\/uploads\/2026\/07\/2026FALL_Sloan-1290x860-1-435x290.jpg 435w\" sizes=\"(max-width: 1290px) 100vw, 1290px\"\/><figcaption>\n<p class=\"attribution\">James Yang\/theispot.com<\/p>\n<\/figcaption><\/figure>\n<div class=\"article-summary\"><strong class=\"article-summary__strong\">\u6982\u8981 <\/strong><\/p>\n<p>While conversational generative AI can be used to test thinking, an agentic system can hold a large volume of data and sustain analyses across entire data sets without losing the thread. Working with agents, executives can define context (what the agent can access), capabilities (what the agent can do), and orientation (what the agent pays attention to). Multiple agents can be configured to do analyses with different orientations against the same data to compare approaches to solving a problem.<\/p>\n<\/div>\n<div class=\"article-narration\">\n<p>    <a href=\"#narration\" id=\"narrationModal\" class=\"j-audio-trigger current-speed\" title=\"Stop Prompting AI. Start Directing It\"><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 \u201cStop Prompting AI. Start Directing It\u201d <span>(25:42)<\/span><\/span><br \/>\n    <\/a>\n<\/div>\n<aside class=\"callout-info\">\n<h4>\u7814\u7a76<\/h4>\n<ul>\n<li>The authors drew on two streams of research for this article. The first was a qualitative study of AI-assisted discovery that identified four pathways by which AI generates surprising insights during analytical work.<a id=\"reflinki\" class=\"reflink\" href=\"#refi\">i<\/a><\/li>\n<li>The second stream was an examination of how organizations function as algorithmic \ufeffassemblages; it showed that algorithmic systems are shaped by what data is made accessible, what capabilities are configured, and how agency is distributed.<a id=\"reflinkii\" class=\"reflink\" href=\"#refii\">ii<\/a><\/li>\n<li>Both studies drew on a broad literature about professional practice and discovery, including work on reflective practice, organizational learning, and the processes by which professionals generate genuinely new understanding.<\/li>\n<\/ul>\n<\/aside>\n<p><span class=\"smr-leadin\">The most valuable<\/span> thing a professional produces is not a faster analysis or a better summary. It is insight: a genuinely new way of seeing a problem, a connection that changes how they understand a situation, or a pattern that nobody has named. Think of a strategy consultant who identifies the real competitive challenge behind a client\u2019s margin erosion, or a team member who notices a silence in the data that everyone else has learned to take for granted.<\/p>\n<p>What makes this kind of discovery hard is that expertise, the very thing that makes professionals effective, also makes certain kinds of insight difficult to reach. The frame that lets them see a problem clearly also shapes what they look for \u2014 and what they stop looking for. But insights that change thinking are often found at the edges of that frame, such as in the friction between competing interpretations.<\/p>\n<p>Conversational AI is already moving in this direction. A well-constructed prompt can surface competing interpretations, expose gaps, and challenge assumptions. But agentic AI \u2014 systems that are configured and directed rather than conversed with \u2014 can take users further still. Unlike a prompted conversation that is bounded by what a human supplies and thinks to ask, an agentic system holds more data and sustains analytical orientations across entire data sets without losing the thread. The discovery moves are the same; the depth is not.<\/p>\n<p>Using agentic AI this way demands a professional skill different from both prompting and automation: knowing how to design systems for insight and how to make sense of what they reveal. We call it <em>directing intelligence<\/em>.<\/p>\n<h3>Two Ways of Working With AI<\/h3>\n<p>Most professionals encounter AI as a conversation: They type a question, evaluate the response, refine, then ask again.<\/p>\n<div class=\"article-authors\" id=\"article-authors\">\n<h4 class=\"article-authors__title\">\u8457\u8005\u306b\u3064\u3044\u3066<\/h4>\n<div class=\"article-authors__bio\">\n<p>Jennifer Sloan worked as a research fellow at UCL School of Management. Vern L. Glaser is a professor of entrepreneurship and family enterprise at the University of Alberta\u2019s Alberta School of Business.<\/p>\n<\/div><\/div>\n<div class=\"article-ref\" id=\"article-ref\">\n<h4 class=\"article-ref__title\">\u53c2\u8003\u6587\u732e<\/h4>\n<div class=\"article-ref__list\">\n<p id=\"refi\"><b>i.<\/b> J. Sloan and \ufeffV.L. Glaser, \u201cRobotic Artistry: Four Surprise Pathways for Generative Artificial Intelligence-Assisted Abductive Theorization,\u201d express manuscript, Strategic Organization, published online April 28, 2026, <a href=\"https:\/\/doi.org\/10.1177\/14761270261448648\" target=\"_blank\">https:\/\/doi.org\/10.1177\/14761270261448648<\/a>.<\/p>\n<p id=\"refii\"><b>ii.<\/b> V.L. Glaser, J. Sloan, and J. Gehman, \u201cOrganizations as Algorithms: A New Metaphor for Advancing Management Theory,\u201d Journal of Management Studies 61, no. 6 (September 2024): 2748-2769, <a href=\"https:\/\/doi.org\/10.1111\/joms.13033\" target=\"_blank\">https:\/\/doi.org\/10.1111\/joms.13033<\/a>.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"article-ack\">\n<h4 class=\"article-ack__title\">\u8b1d\u8f9e<\/h4>\n<div class=\"article-ack__copy\">\n<p>This research forms part of the UK Research and Innovation project \u201cInnovating Across Sectors\u201d (MR\/Y034430\/1; PI: Angela Aristidou). The analyses and conclusions presented here are those of the authors, not of the funding body.<\/p>\n<\/div><\/div>\n<div class=\"article-doi\">\n    <a href=\"https:\/\/doi.org\/10.63383\/PVzT4379\" target=\"_blank\" class=\"article-doi__number\">https:\/\/doi.org\/10.63383\/PVzT4379<\/a>\n<\/div>\n<\/div><\/div>\n<p>#Stop #Prompting #Start #Directing<\/p>","protected":false},"excerpt":{"rendered":"<p>Research Feature Conversational AI speeds up familiar work. Configuring AI to interrogate your data \u2014 what the authors call directing intelligence \u2014 surfaces insights that familiar ways of working tend to miss.&#13; Jennifer Sloan and Vern L. Glaser August 05, 2026 Reading Time: 19 min\u00a0 James Yang\/theispot.com Summary: While conversational generative AI can be used to test thinking, an agentic system can hold a large volume of data and sustain analyses across entire data sets without losing the thread. Working with agents, executives can define context (what the agent can access), capabilities (what the agent can do), and orientation (what the agent pays attention to). Multiple agents can be configured [&hellip;]<\/p>","protected":false},"author":1,"featured_media":8874,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[9],"tags":[],"class_list":["post-8873","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>Stop Prompting AI. 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