New research from PYMNTS Intelligence\u2019s \u201cThe Enterprise AI Benchmark Report\u201d<\/a> reveals that over 7 in 10 executives (71%) at companies with $1 billion or more in annual revenue believe that organizational readiness is the primary limitation on AI performance. Meanwhile, just 11% think that AI technology itself is the main barrier.<\/p>\n Advertisement: Scroll to Continue<\/p>\n In other words, nearly all executives surveyed agreed AI can add value to their company. But most also feel that internal bottlenecks are holding things back. \u201cWhat\u2019s really holding it back is that most AI tools don\u2019t learn and don\u2019t integrate well into workflows,\u201d a report<\/a> from MIT report said last July.<\/p>\n \u00a0<\/p>\n The Readiness Challenge<\/p>\n The biggest limitation enterprises face is rarely AI technology itself \u2014 it\u2019s usually the company\u2019s ability to harness it. <\/p>\n The gap between AI\u2019s theoretical capabilities and real-world impact is increasingly tangible across business units at large enterprises. Finance wants more accurate forecasting and streamlined quarterly reporting, but the data is spread across dashboards and databases with mismatched formats. Sales wants AI to draft proposals, but customized CRM modules often require manual inputs. Customer support wants automation, but the source of its policies lives in PDFs and email threads. Only 5% of enterprises have AI tools integrated in workflows at scale, the MIT report found. Seven out of 9 sectors \u2014 the exceptions are technology and media \u2014 show no real structural change.<\/p>\n In each case, AI exposes bottlenecks that are organizational. That in turn can focus C-suite attention on the areas where the technology can have the greatest impact. Most companies are seeing benefits from using AI in compliance, risk management and quality control, according to a report<\/a> by ISG. As for fueling growth and reducing costs? Only around 1 in 4 AI initiatives is meeting the C-suite\u2019s expectations for revenue impact.<\/p>\n \u201cThe real issue is not just whether a company can use AI. It\u2019s whether they know where AI should be used, and where it shouldn\u2019t,\u201d Schein said. He added that the companies that will get the most value aren\u2019t applying AI in a spray-and-pray fashion. \u201cThey\u2019re using it where it creates real leverage and avoiding it where a simpler, cheaper, or more deterministic approach already works,\u201d he said.<\/p>\n We\u2019d love to be your preferred source for news<\/a>.<\/p>\n Please add us to your preferred sources list so our news, data and interviews show up in your feed. Thanks!<\/p>\n It\u2019s Not Just Cost<\/p>\n To dig deeper, we asked executives which specific barriers they think are limiting AI performance at their firm. Perhaps unsurprisingly, issues related to company data quality, availability or fragmentation came up the most often, cited by 63% of executives. This reflects the challenges of using AI across databases and other sources of information that are not always interoperable or in compatible formats.<\/p>\n Budget, time and other resource constraints ranked second, cited by 49% of executives as limiting AI performance at their firms. But interestingly, about the same share named governance, risk and approval processes (48%) and lack of clear ownership and accountability (46%).<\/p>\n \u00a0<\/p>\n Just 30% of organizations are redesigning key processes around AI and fewer than 4 in 10 report using the technology \u201cat a surface level, with little or no change to underlying business processes,\u201d a report<\/a> from Deloitte found in January.<\/p>\n Company decisions often come down to cost and return on investment targets. But it\u2019s significant that executives are equally focused on institutional pieces of the AI equation.<\/p>\n Nearly half (45%) of the executives surveyed by PYMNTS cited systems and workflows as a barrier for AI performance. Almost the same share pointed to internal skills and talent (42%) and to lack of leadership or alignment or sponsorship (40%) as holding back the positive impact of AI.<\/p>\n Zooming out, our data makes clear that the enterprise AI story has shifted from \u201cWhat can the technology do?\u201d to \u201cHow can organizations roll out and use AI most effectively?\u201d The companies that get disproportionate value won\u2019t be the ones trying to put AI everywhere, but the ones that treat data, governance and ownership as the real AI stack \u2014 and build the muscle to deploy it consistently.<\/p>\n![\"Preferred](\"https:\/\/www.pymnts.com\/wp-content\/uploads\/2026\/02\/Google-PYMNTS-blackbox.svg\")
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