Jake Cantu
Partner & Managing Director, Global Leader, Technology, Media, and Telecommunications
Chicago
AI is reshaping how enterprise software is sold and priced, forcing a fundamental redefinition of what software companies actually deliver, and leaving the go-to-market playbook in a state of significant disruption. Specifically, sales teams are deploying AI tools across marketing, pipeline management, and customer success, while struggling to demonstrate improved win rates amid fragmented solutions and poor underlying data. At the same time, AI-native competitors are disrupting established categories with outcome-based pricing, charging only when customers realize tangible value. All told, the commercial models that powered two decades of SaaS growth are proving incompatible with AI's economics. Companies that can respond to these transitions will capture market advantage. Those clinging to legacy approaches will watch their customers defect.
AI is transforming enterprise software sales processes far beyond automated customer support. Major software makers are putting AI tools directly into their products, lowering adoption barriers and normalizing AI as default functionality. Competition accelerates the trend: as first-movers demonstrate measurable improvements in win rates and deal velocity, pressure builds for others to follow.
Significant obstacles remain to the broader deployment of AI-enabled sales tools. Many teams lack the clean data AI systems require; leaders struggle to demonstrate ROI; and first-generation tools remain fragmented across functions. The strategic imperative is to recognize that successful AI adoption is not a matter of procurement but organizational transformation. AI requires new measurements, new processes, and new training. Success will come from execution, not merely adoption.
Enterprise software is undergoing its second major pricing transformation in fifteen years. The first came when the industry moved from one-time licenses to subscriptions (the SaaS era). Now AI-enabled solutions are driving a new paradigm: usage- and outcome-based pricing.
Per-seat charges are poorly suited to how AI creates value—when one AI customer service system might perform work equivalent to 700 human agents, traditional pricing norms buckle. AI-native startups are already charging only when customers realize tangible value, offering buyers implicit ROI guarantees while threatening legacy vendors' recurring revenue streams.
A strong response requires more than pricing experimentation. Companies should redefine their role from "vendor" to "partner," investing in customer success as a core capability. Features should give way to outcomes. The per-seat era is ending, but recurring revenue doesn't have to disappear with it.
Explore more from the 2026 Enterprise software technology predictions report in our other chapters
2026 Enterprise software technology predictions report
In this 2026 Enterprise software predictions report, we examine seven critical dynamics reshaping the enterprise software landscape and explain the specific transformations companies should execute to respond effectively.
These predictions reflect the inflection points we clearly observe across the industry, as AI forces fundamental changes across software development, interfaces, trust architectures, go-to-market operations, pricing models, valuation frameworks, and business structure itself.
We believe that companies mastering these transitions will define the next era of enterprise software leadership, and we predict that those unable to adapt will be sidelined as the industry landscape redraws itself.
