![\"Using](\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/08\/1786237571_323_0x0.jpg\")
<\/p>\n<\/p>\n
The next wave of enterprise AI value may depend less on what vendors can build and more on how closely they build it with customers.<\/p>\n
getty<\/p>\n
Demand for enterprise AI continues to climb and accelerate. In response, software providers are stepping up, shipping more features at a faster pace. This dynamic suggests a win-win scenario; one where customers are getting new AI-based capabilities and vendors are maintaining and strengthening their product relevancy. <\/p>\n
However, the results of a recent survey<\/a> paint a less obvious picture. While software companies are delivering code at a frenetic clip, it turns out that for 51 percent of them, fewer than one in four customers are using what\u2019s been built.<\/p>\n The problem doesn\u2019t appear to be demand. It\u2019s increasingly a problem of readiness, alignment, and the ability to translate AI into measurable business value. This finding provides valuable and urgent lessons for enterprise leaders and software providers alike.<\/p>\n Enterprises Want AI, But Not Just Any AI<\/p>\n Max Risen is the co-founder and president of M&A at Banyan Software<\/a>, a company that owns and manages over 120 vertical market software (VMS) companies. These are businesses that provide highly specialized feature sets for specific industries such as software to help run a health clinic on a college campus. <\/p>\n Max Risen, President, M&A at Banyan Software<\/p>\n Banyan Software<\/p>\n To serve his portfolio of VMS operators, Risen developed a survey to understand how the marketplace was responding to their approach to AI feature development and deployment. <\/p>\n He knew VMS businesses were not immune to the outsized momentum of AI but wanted to derive any unique insights when compared with what was being experienced by the well-known, large enterprise software companies. <\/p>\n More than 260 VMS companies responded and the results were surprising. A core finding was that 51 percent of software providers reported that fewer than one in four customers were using the AI capabilities they had built.<\/p>\n VMS operators were creating and deploying code quickly and customers were expressing their high interest in AI use but there was a notable misalignment.<\/p>\n Building AI Faster Doesn\u2019t Mean Customers Will Use It<\/p>\n One characteristic of the emergent intelligence age is that software can be developed, tested, and deployed at a far higher velocity than in the past. That\u2019s largely a good news story given a history of enterprise software that has moved slower than market demand. <\/p>\n One consequence of faster software deployment is that customers get a lot more features quickly, but they may not be what end users want. Risen\u2019s survey validates this.<\/p>\n A larger volume of smart software might sound like a gift to the enterprise, but in the short term this is presenting more challenges than it may intuitively seem.<\/p>\n Enterprise customers want AI, but they are still hesitant to adopt AI quickly for change management reasons that include concerns about integration with existing workflows, security and privacy risks, and the nondeterministic nature of many generative AI systems. <\/p>\n Most importantly, while businesses want AI capability, many don\u2019t yet know how best to think about using and getting value from it. After all, large-scale adoption in the enterprise, particularly with VMS solutions, is fairly recent. <\/p>\n Using More AI Doesn\u2019t Mean Creating More Value<\/p>\n