As AI becomes embedded across enterprise software, vendors are finding that no single pricing model is sufficient to reflect the variation in cost, usage, and value it creates. Traditional seat-based pricing is increasingly rigid in this context, as AI-driven features introduce variable consumption patterns and non-linear value delivery. This is driving a shift toward more flexible approaches, including tiered pricing, credit-based systems, and early-stage experiments with outcome-based charging. The core challenge is designing models that remain commercially viable while reflecting how customers actually use AI-powered capabilities.

At the same time, customer expectations around pricing are becoming more exacting. Procurement and finance teams are demanding clearer connections between what they pay and the value they receive, particularly as AI usage becomes more variable and harder to forecast. This is forcing vendors to rethink how they structure and communicate pricing, but most are still in an iterative phase – blending bundles, credits, and usage-based elements in different ways without a settled industry standard.

This webinar is designed to bring structure to that evolution. Verdantix has been tracking how enterprise software pricing is adapting as AI moves into core product functionality, and clear patterns are beginning to emerge despite the noise. Drawing on our upcoming report, 'Market Insight: Rethinking SaaS Pricing Models In An AI Age', our analysts will break down the main pricing models in use today, where the market is converging, and how vendors can think about selecting and combining models in practice.