{"id":1485,"date":"2026-08-31T09:00:00","date_gmt":"2026-08-31T13:00:00","guid":{"rendered":"https:\/\/aiinstitute.hbs.edu\/future-proof-with-ai\/?p=1485"},"modified":"2026-08-24T15:38:22","modified_gmt":"2026-08-24T19:38:22","slug":"memo-september-2026","status":"publish","type":"post","link":"https:\/\/aiinstitute.hbs.edu\/future-proof-with-ai\/memo-september-2026\/","title":{"rendered":"Three Tips and One Warning When Measuring What AI Returns"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Last month we discussed the surprise AI token bills and responses to it. This month we ask what the spending buys. In recent conversations with my executive education students and clients, across sectors and around the world, the exploding cost of AI has been the dominant theme. But the people paying for it and the people using it don\u2019t agree: executives want the number down, while managers running software development, deal sourcing and due diligence, audit and compliance, and sales and marketing are still asking to maintain \/ raise the per-person budget. Below are three pointers that can help you arrive at a number both sides will accept, and the one thing I urge you never to do.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Tip One: Put Accountability with an Exec<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">This year&#8217;s ROI research highlights outcome accountability as the single biggest determinant of AI returns. KPMG&#8217;s Q2 Global AI Pulse survey of 2,145 leaders across twenty markets found that only 24% of organizations place ultimate AI accountability with the CEO or executive committee. Where they do, performance diverges sharply: 57% realize meaningful business value (vs. 21% elsewhere) and 14% report established ROI (vs. 4%). [1] Companies with clear executive accountability are far better positioned to scale AI successfully, and the differentiator is not necessarily higher funding, which holds steady at a $188 million average across all firms, but rigorous cost visibility and operational discipline.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Reporting lines rarely move numbers this much; this one does because measurement is inherently cross-functional. Proving value requires Finance to agree on baselines, IT to supply usage data, and business units to concede alternative outcomes.<strong> <\/strong>Compelling that coordination requires the unique authority of the CEO. Without it, efforts fracture: a separate survey of 365 senior leaders found 58% naming fragmented ownership as their primary barrier to measuring AI performance [2].<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Tip Two: Measure Cost per Finished Task<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><a><\/a>Shift AI metrics from tracking inputs (licenses, tokens, usage) to the cost per successful task; that is, the total expense to produce one finalized, usable piece of work. This automatically captures AI&#8217;s three biggest &#8220;value leaks&#8221; without complex tracking models:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Botsitting:<\/strong> Employees spending the time AI supposedly saved to feed context or fix mistakes. Redoing a task can significantly up the cost for a single output.<\/li>\n\n\n\n<li><strong>Attenuation:<\/strong> When AI generates volume that never translates to value (e.g., MIT showed coding agents boosted commits by 180%, but shipped releases rose only 30%). [3]<\/li>\n\n\n\n<li><strong>Agentic Loops:<\/strong> Chains of model calls that endlessly burn compute without converging on a useful answer.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">By measuring final, accepted outputs, you automatically account for the hidden costs of getting there.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Yet none of this is measurable without spend visibility. KPMG found that 42% of leaders have only partial visibility into AI spending, a third cite difficulty understanding AI cost structures\u2014 including token-based pricing\u2014and 13% have visibility only after billing. Fixing that blind spot is decisive: organizations with full visibility into AI operating costs are five times more likely to report established ROI (15% versus 3%).<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Tip Three: Measure at Two Levels<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">No project-level ROI figure will tell you whether the aggregate spend is justified, so stop trying to construct one. Measure above and below the projects instead.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Above the project, use revenue per employee. It is already in your financials, already audited, and immune to the vanity metrics that make AI dashboards easy to manipulate. When the ratio climbs while headcount holds flat or falls, the investment is producing output. The aggregate picture is striking: the 2026 Fortune 500 posted a record $687,000 in revenue per employee. Total headcount fell 1% as aggregate revenue grew 5%, profits jumped 12%, and market cap climbed 19%. This second consecutive annual decline\u2014historically seen only during or after recessions\u2014realizes the ultimate scaling goal: growing revenue while shrinking headcount. [4]<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Below the project, run a portfolio, as outlined in a January <em>Harvard Business Review<\/em> framework. [5] Its power lies in a dual lens: an advancement pipeline with explicit stage gates, and a whole-portfolio dashboard balancing risk, return, time horizons, and strategic alignment.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Backlog items are scored &#8220;buy, sell, or hold&#8221; against strategic fit, feasibility, and resources. Projects progress through four stages\u2014outline, partner, experiment, and scale\u2014each requiring strict go\/no-go gates for data governance, talent, process redesign, and business-case viability. Lloyds Banking Group runs a version of this as a cross-functional &#8220;GenAI Control Tower.&#8221; [5] Ultimately, a portfolio can be dynamically rebalanced; a pile of pilots cannot.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The One Thing to Never Do<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">I&#8217;m out of space here, so stay tuned for Part 2 of this Tech Memo next month. It will include one thing to never do, rounding out our discussion of measuring AI ROI, plus our monthly action item for leaders, one other thing to consider in October, and a preview of November.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Sources<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">[1] KPMG International, &#8220;Growing adoption signals progress as cost visibility and accountability drive AI value,&#8221; Global AI Pulse Survey Q2 2026 \u2014 2,145 C-suite and senior leaders across 20 markets, fielded April 28\u2013May 25, 2026. <a href=\"https:\/\/kpmg.com\/xx\/en\/media\/press-releases\/2026\/06\/growing-adoption-signals-progress-as-cost-visibility-and-accountability-drive-ai-value.html\">https:\/\/kpmg.com\/xx\/en\/media\/press-releases\/2026\/06\/growing-adoption-signals-progress-as-cost-visibility-and-accountability-drive-ai-value.html<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">[2] Larridin \/ TrendCandy, &#8220;2026 State of Enterprise AI,&#8221; survey of 365 senior leaders at companies with 1,000+ employees, January 2026. <a href=\"https:\/\/www.businesswire.com\/news\/home\/20260203918939\/en\/\">https:\/\/www.businesswire.com\/news\/home\/20260203918939\/en\/<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">[3] Mert Demirer, Leon Musolff, and Liyuan Yang, &#8220;Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools,&#8221; NBER Working Paper 35275, May 2026, <a href=\"https:\/\/www.nber.org\/papers\/w35275\">https:\/\/www.nber.org\/papers\/w35275<\/a>; discussed in John Burn-Murdoch, &#8220;How much value is AI really creating?,&#8221; Financial Times, June 6-7, 2026.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">[4] Fortune 500 2026 analysis: record revenue and profit per employee alongside a second consecutive year of headcount decline, June 19, 2026. <a href=\"https:\/\/finance.yahoo.com\/economy\/articles\/record-revenues-record-profits-record-114119350.html\">https:\/\/finance.yahoo.com\/economy\/articles\/record-revenues-record-profits-record-114119350.html<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">[5] Faisal Hoque, Erik Nelson, Thomas H. Davenport, and Paul Scade, &#8220;<a>Manage Your AI Investments Like a Portfolio,&#8221; Harvard Business Review, January 21, 2026 (Reprint H091DR<\/a>). <a href=\"https:\/\/hbr.org\/2026\/01\/manage-your-ai-investments-like-a-portfolio\">https:\/\/hbr.org\/2026\/01\/manage-your-ai-investments-like-a-portfolio<\/a><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Meet the Author<\/strong><\/h2>\n\n\n\n<div class=\"wp-block-media-text is-stacked-on-mobile\" style=\"grid-template-columns:42% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"400\" src=\"http:\/\/aiinstitute.hbs.edu\/future-proof-with-ai\/wp-content\/uploads\/sites\/42\/2026\/03\/Mike-Grandinetti-Headshot.jpeg\" alt=\"\" class=\"wp-image-1179 size-full\" srcset=\"https:\/\/aiinstitute.hbs.edu\/future-proof-with-ai\/wp-content\/uploads\/sites\/42\/2026\/03\/Mike-Grandinetti-Headshot.jpeg 400w, https:\/\/aiinstitute.hbs.edu\/future-proof-with-ai\/wp-content\/uploads\/sites\/42\/2026\/03\/Mike-Grandinetti-Headshot-300x300.jpeg 300w, https:\/\/aiinstitute.hbs.edu\/future-proof-with-ai\/wp-content\/uploads\/sites\/42\/2026\/03\/Mike-Grandinetti-Headshot-150x150.jpeg 150w, https:\/\/aiinstitute.hbs.edu\/future-proof-with-ai\/wp-content\/uploads\/sites\/42\/2026\/03\/Mike-Grandinetti-Headshot-160x160.jpeg 160w\" sizes=\"auto, (max-width: 400px) 100vw, 400px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"wp-block-paragraph\">Mike Grandinetti is an Executive Fellow at Harvard Business School. He\u2019s a serial tech entrepreneur, board member, AI &amp; innovation consultant, VC EIR, and award-winning professor in the practice. A former Silicon Valley engineer and McKinsey consultant, Mike has been C-Suite leader roles across 8 tech startups, resulting in 2 NASDAQ IPOs and 7 strategic exits.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">He\u2019s led senior executive workshops for Berkeley, Brown, Carnegie Mellon, Columbia, Cornell, Harvard P&amp;ED, NYU &amp; Oxford. He&#8217;s been a senior advisor and organizing team member for the MIT CIO Symposium for a decade.<\/p>\n<\/div><\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.linkedin.com\/in\/mikegrandinetti\">https:\/\/www.linkedin.com\/in\/mikegrandinetti<\/a><br><a href=\"http:\/\/www.mikegrandinetti.com\" id=\"www.mikegrandinetti.com\">www.mikegrandinetti.com<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In recent conversations with my executive education students and clients, across sectors and around the world, the exploding cost of AI has been the dominant theme. In this memo you&#8217;ll find three pointers that can help you navigate AI spending and ROI.<\/p>\n","protected":false},"author":19325,"featured_media":1486,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_trash_the_other_posts":false,"rkv_hide_featured_image":false,"rkv_hide_page_title":false,"rkv_hide_abstract_shapes":true,"rkv_reduce_header":false,"hbsd3_featured_media_url":"","hbsd3_featured_media_url_autoplay":false,"editor_notices":[],"footnotes":""},"categories":[1],"tags":[],"tax_cop":[],"rkv-people-shadow":[8],"insight_type":[],"class_list":["post-1485","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Three Tips and One Warning When Measuring What AI Returns - Future Proof with AI<\/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:\/\/aiinstitute.hbs.edu\/future-proof-with-ai\/memo-september-2026\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Three Tips and One Warning When Measuring What AI Returns - Future Proof with AI\" \/>\n<meta property=\"og:description\" content=\"In recent conversations with my executive education students and clients, across sectors and around the world, the exploding cost of AI has been the dominant theme. 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