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Good morning. Companies are betting on AI\u2014yet nearly all enterprise pilots are stuck at the starting line.<\/p>\n
The GenAI Divide: State of AI in Business 2025<\/em>, a new report published by MIT\u2019s NANDA initiative, reveals that while generative AI holds promise for enterprises, most initiatives to drive rapid revenue growth are falling flat.<\/p>\n Despite the rush to integrate powerful new models, about 5% of AI pilot programs achieve rapid revenue acceleration; the vast majority stall, delivering little to no measurable impact on P&L. The research\u2014based on 150 interviews with leaders, a survey of 350 employees, and an analysis of 300 public AI deployments\u2014paints a clear divide between success stories and stalled projects.<\/p>\n To unpack these findings, I spoke with Aditya Challapally, the lead author of the report, and a research contributor to project NANDA at MIT.<\/p>\n \u201cSome large companies\u2019 pilots and younger startups are really excelling with generative AI,\u201d Challapally said. Startups led by 19- or 20-year-olds, for example, \u201chave seen revenues jump from zero to $20 million in a year,\u201d he said. \u201cIt\u2019s because they pick one pain point, execute well, and partner smartly with companies who use their tools,\u201d he added.<\/p>\n But for 95% of companies in the dataset, generative AI implementation is falling short. \u201cThe 95% failure rate for enterprise AI solutions represents the clearest manifestation of the GenAI Divide,\u201d the report states. The core issue? Not the quality of the AI models, but the \u201clearning gap\u201d for both tools and organizations. While executives often blame regulation or model performance, MIT\u2019s research points to flawed enterprise integration. Generic tools like ChatGPT excel for individuals because of their flexibility, but they stall in enterprise use since they don\u2019t learn from or adapt to workflows, Challapally explained.<\/p>\n The data also reveals a misalignment in resource allocation. More than half of generative AI budgets are devoted to sales and marketing tools, yet MIT found the biggest ROI in back-office automation\u2014eliminating business process outsourcing, cutting external agency costs, and streamlining operations.<\/p>\n How companies adopt AI is crucial. Purchasing AI tools from specialized vendors and building partnerships succeed about 67% of the time, while internal builds succeed only one-third as often.<\/p>\n This finding is particularly relevant in financial services and other highly regulated sectors, where many firms are building their own proprietary generative AI systems in 2025. Yet, MIT\u2019s research suggests companies see far more failures when going solo.<\/p>\n Companies surveyed were often hesitant to share failure rates, Challapally noted. \u201cAlmost everywhere we went, enterprises were trying to build their own tool,\u201d he said, but the data showed purchased solutions delivered more reliable results.<\/p>\n Other key factors for success include empowering line managers\u2014not just central AI labs\u2014to drive adoption, and selecting tools that can integrate deeply and adapt over time.<\/p>\n Workforce disruption is already underway, especially in customer support and administrative roles. Rather than mass layoffs, companies are increasingly not backfilling positions as they become vacant. Most changes are concentrated in jobs previously outsourced due to their perceived low value.<\/p>\n The report also highlights the widespread use of \u201cshadow AI\u201d\u2014unsanctioned tools like ChatGPT\u2014and the ongoing challenge of measuring AI\u2019s impact on productivity and profit.<\/p>\n Looking ahead, the most advanced organizations are already experimenting with agentic AI systems that can learn, remember, and act independently within set boundaries\u2014offering a glimpse at how the next phase of enterprise AI might unfold.<\/p>\n Sheryl<\/strong>Estrada<\/strong> Michael A. Discenza<\/b> was appointed VP and CFO of <\/span>The Timken Company<\/span> (NYSE: TKR), effective immediately. Discenza has 25 years of experience at Timken in roles of increasing responsibility, including the last 10 as VP of finance, and group controller.<\/span><\/p>\n John Cole<\/b> was appointed CFO of <\/span>ELB Learning<\/span>, a provider of immersive learning solutions. He brings more than 25 years of experience leading finance and operations for Fortune 100 and 500 companies, according to ELB. Cole aims to strengthen the financial infrastructure to support the company\u2019s next phase of growth.<\/span><\/p>\n The report\u2019s findings are based on a survey of more than 1,500 manufacturing leaders across 17 major manufacturing countries. Cybersecurity now ranks among the top external risks, second only to inflation and economic growth. One-third of respondents hold responsibilities spanning both information technology (IT) and operational technology (OT) cybersecurity.<\/p>\n Nearly half (48%) of cybersecurity professionals identified securing converged architectures as key to positive outcomes over the next five years, compared to just 37% of all respondents.<\/p>\n However, a shortage of skilled talent, training challenges, and rising labor costs remain major hurdles. As manufacturers recruit the next generation, cybersecurity and analytical skills are becoming hiring priorities\u2014reinforcing the need to align technical innovation with human development, according to the report.<\/p>\n<\/div>\n \u201cEvery single Monday was called ‘AI Monday.’ You couldn\u2019t have customer calls, you couldn\u2019t work on budgets, you had to only work on AI projects.\u201d<\/strong><\/p>\n \u2014Eric Vaughan, CEO of enterprise software company IgniteTech, told Fortune<\/em> in an interview that he established a mandate: on Mondays, staff could only work on AI. In early 2023, convinced generative AI was an \u201cexistential\u201d transformation, Vaughan saw that his team was not fully on board. His ultimate response? He replaced nearly 80% of the staff within a year, according to headcount figures reviewed by Fortune<\/em>.<\/p>\n<\/div>\n #MIT #report #generative #pilots #companies #failing<\/p>\n","protected":false},"excerpt":{"rendered":" Good morning. Companies are be… <\/p>\n","protected":false},"author":1,"featured_media":4062,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2],"tags":[529,526,528,527,530,532,531,533],"_links":{"self":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts\/4061"}],"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=4061"}],"version-history":[{"count":0,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts\/4061\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/media\/4062"}],"wp:attachment":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4061"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4061"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4061"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}What\u2019s behind successful AI deployments?<\/strong><\/h3>\n
sheryl.estrada@fortune.com<\/p>\nLeaderboard<\/h3>\n
Big Deal<\/h3>\n
Modern manufacturing relies heavily on connected devices and industrial control systems, which are prime targets for cyberattacks. For protection, manufacturers are increasingly turning to AI to help manage these risks, according to the\u00a0State of Smart Manufacturing Report<\/em>\u00a0by Rockwell Automation, Inc.<\/p>\nGoing deeper<\/h3>\n
In a new Fortune<\/em>opinion piece,\u00a0“Future CEOs, erased: the economic cost of losing Black women in the workforce,”\u00a0Katica Roy, the CEO and founder of the Denver-based Pipeline, a SaaS company, explains\u00a0the implications of\u00a0almost 300,000 Black women exited the labor force so far this year\u2014thinning a pipeline that was already too narrow.<\/div>\n\n“This isn\u2019t a seasonal fluctuation or statistical footnote. It\u2019s a strategic failure with long-term consequences,” Roy writes. “Black women have long been a cornerstone of America\u2019s economic engine\u2014driving participation, powering key industries, and anchoring family incomes. Now, that foundation is fracturing. And the fallout is more than short-term\u2014it\u2019s a direct threat to corporate succession planning, innovation, and growth. The U.S. economy has always depended on Black women\u2019s labor. In fact, no group of women in America has historically had higher labor force participation than Black women.”<\/div>\n<\/div>\nOverheard<\/h3>\n