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If the current frenzy over artificial intelligence feels familiar to Peter Cappelli, the George W. Taylor professor of management at the Wharton School, it\u2019s because he\u2019s seen this movie before. He points to the period between 2015 and 2017, when major consultancies and the World Economic Forum confidently predicted that driverless trucks would eliminate truck drivers within a few years.<\/p>\n
\u201cYou didn\u2019t have to think very long to realize that just wasn\u2019t going to make sense in practice,\u201d Cappelli told Fortune<\/em> on Zoom from his home in Philadelphia. <\/p>\n \u201cYou didn\u2019t have to think very long about driverless trucks to think about, okay, what happens when they need gas? You know? Or what happens if they have to stop and make a delivery? And if they have to have an employee sitting with them, of course it defeats the purpose, right?\u201d<\/p>\n Cappelli, who recently partnered with Accenture on a series of podcasts to get to the bottom of what AI is actually doing to jobs, warned against listening too closely to the companies that are talking their book, or trying to sell you on their new products.<\/p>\n \u201cIf you\u2019re listening to the people who make the technology, they\u2019re telling you what\u2019s possible, and they\u2019re not thinking about what is practical.\u201d <\/p>\n Over the course of a wide-ranging conversation with Fortune<\/em>, Cappelli tackled what AI is really doing to work, much like he talked to Fortune<\/em> previously about how remote work is, actually, quite bad for most organizations.<\/p>\n \u201cI mean, people say I\u2019m a contrarian,\u201d Cappelli said, \u201cbut I don\u2019t think so, so much as I just am skeptical about stuff, you know?\u201d <\/p>\n When pointed out this was an inherently contrarian position, Cappelli laughed, before returning to the main point. \u201cI just get nervous with hype.\u201d <\/p>\n He talked to Fortune<\/em> about how his research fits into the wider picture that defined the back half of 2025, after the influential MIT study that caught the eye on 95% of generative AI pilots failing to generate any meaningful return. His favorite example was a particular case study on a company that actually made AI work, both cutting headcount and boosting productivity. It still didn\u2019t fit neatly with predictions (say, from Elon Musk or Anthropic\u2019s Dario Amodei, that work will soon be optional, or even a hobby). \u201cIt\u2019s hugely expensive to do this,\u201d Cappelli said about his findings. \u201cAnd this was a success.\u201d<\/p>\n Cappelli detailed the findings of a case study that he participated in, published in the Harvard Business Review, on Ricoh, an insurance claims processor: the exact type of low-level administrative work that AI is supposed to automate easily. The reality of adoption, however, was a financial shock. While the company eventually achieved three times the performance, the transition was anything but cheap. The firm spent a year with a team of six, three of whom were expensive outside consultants, just to get the system running.<\/p>\n \u201cThe first thing they discovered,\u201d Capelli said, \u201cis large language models could do this pretty well \u2014\u00a0at three times the cost of their employees doing it [manually]. Okay, so that\u2019s not going to work.\u201d Cappelli pointed out that the costs included Ricoh paying roughly $500,000 in fees to outside consultants.<\/p>\n Even after optimizing the process, Ricoh was still spending about $200,000 a month on AI fees\u2014more than their total payroll for the task had been. They were able to cut their headcount from 44 to 39, he added, showing just how far from being a massive job killer AI is in practice. His explanation recalls his self-driving truck example.<\/p>\n \u201cThe reason they still need employees is that lots of problems have to be chased down, and they\u2019re harder to chase down if they come off of AI,\u201d he said. The good news, he added, is that this Ricoh division will ultimately be three times as productive.<\/p>\n \u201cSo that\u2019s the payoff, but it\u2019s not cheap [and] it took a hell of a long time to do.\u201d <\/p>\n Ashok Shenoy, VP of Ricoh\u00a0USA, told Fortune<\/em> that, after starting to use AI for \u201cvery routine, repetitive, high-volume tasks,\u201d work for humans didn\u2019t disappear, but \u201cshifted toward areas where human judgment and experience add the most value.\u201d In the year or so since the case study was conducted, he noted that Ricoh has successfully applied AI to mid-level, repetitive, time-consuming tasks at scale, and expects to use AI agents to achieve partial or full workflow automation within the next six to 12 months, \u201cwith a human-in-the-loop to\u00a0resolve missing or unclear information and ensure quality.\u201d<\/p>\n While acknowledging the big-ticket costs highlighted by Cappelli, Shenoy noted that this project reached break-even in less than a year, and it\u2019s $200,000 monthly costs are less expensive than the previous operating model. \u201cThe shift to AI delivered an estimated 15% total cost reduction, even though it did not rely on significant labor cuts.\u201d Regarding headcount, he said \u201cthis exercise was not driven by cost or headcount reduction,\u201d and AI implementation requires creating new roles, redesigning existing ones, and repurposing team members toward higher-value work. He said there haven\u2019t been further job cuts, either, with staffing levels largely stabilizing as productivity increased and volumes grew. \u201cThe bigger change was in how people spent their time. They are doing less repetitive work and are more focused on resolving exceptions, maintaining quality and serving customers.\u201d<\/p>\n Cappelli said he found similar dynamics in his partnership with Accenture, which looked at Mastercard, Royal Bank of Scotland, and Jabil. \u201cThese are all success stories,\u201d he said, and in the long run, they will see productivity will go up. Companies will be able to do more with fewer people but \u201cit\u2019ll take a long while to get there.\u201d He argued that something crucial is being underestimated. \u201cThe key thing, though, is just how much work is involved in doing it.\u201d<\/p>\n Also, regarding headcount reductions, Cappelli said that at least in the areas that he researched, which were specific units within each company, he didn\u2019t see any job cuts whatsoever. When contacted for comment by Fortune, Accenture said it largely agrees with Cappelli\u2019s conclusions, and referred back to CEO Julie Sweet\u2019s recent interview with Fortune<\/em> Editor-in-Chief Alyson Shontell. <\/p>\n According to Cappelli, so much of the noise around AI\u2014and the distance between what\u2019s possible and what\u2019s practical\u2014is driven by what other commentators have called \u201cAI shame.\u201d <\/p>\n Cappelli wasn\u2019t familiar with the \u201cAI shame\u201d phrase, but told Fortune<\/em> it was \u201cabsolutely right\u201d in describing what he\u2019s seen. \u201cThey\u2019re pretending so they can say they\u2019re doing something, right?\u201d he said. \u201cSo the pressure is just enormous on them to try to make this stuff work, because the investors love the idea.\u201d<\/p>\n The professor cited the Harris Poll\u2019s finding in early 2025 that 74% of CEOs globally felt they\u2019d lose their job in two years if they couldn\u2019t demonstrate AI success, and roughly a third said they were performatively adopting AI without really understanding what it would entail. As The Harris Poll put it: \u201cCEOs estimate that over a third (35%) of their AI initiatives amount to mere \u2018AI washing\u2019 for optics and reputation, but offering little to no real business value at all.\u201d<\/p>\n Cappelli described how markets typically celebrate news of layoffs, and even cited research that \u201cphantom layoffs\u201d get announced by companies that never actually occur, because companies are arbitraging the positive stock-market reaction to the news of a potential layoff.<\/p>\n Cappelli predicted a \u201cslow learning curve\u201d will take place, in which CFOs will start realizing \u201cthis is super-expensive stuff to put in place.\u201d The problem, according to Cappelli, is that U.S. management has become \u201cspoiled\u201d and increasingly averse to the hard work of organizational change. <\/p>\n \u201c[Employers] think it should be free. It should be cheap. You should just be able to hang a shingle out, and the right people will just show up,\u201d he says. Real AI success, in his opinion, will require \u201cold-fashioned human resources\u201d work: mapping workflows, breaking down jobs into tasks, and having employees work alongside AI \u201cagents\u201d to refine prompts.<\/p>\n \u201cYou can\u2019t do it over the top of employees, because the employees really do know how their job is done,\u201d Cappelli said. The professor was withering about what he sees happening in most C-suites, saying they are largely \u201cducking\u201d the problem of really grappling with this technology.<\/p>\n \u201cThey\u2019re not seeing it as an organization change problem and a big one,\u201d he said. \u201cThey\u2019re just stressing everybody out and, you know, hoping that it somehow works itself out.\u201d<\/p>\n<\/div>\n #Arrow #Button #Icon<\/p>\n","protected":false},"excerpt":{"rendered":" If the current frenzy over art… <\/p>\n","protected":false},"author":1,"featured_media":11107,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2],"tags":[3816,3817,928,3818],"_links":{"self":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts\/11106"}],"collection":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=11106"}],"version-history":[{"count":0,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts\/11106\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/media\/11107"}],"wp:attachment":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11106"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11106"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11106"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Three times the cost<\/h2>\n
Performative AI shame in the boardroom<\/h2>\n