From SaaS to AI: Why Go-To-Market Models Are Being Rewritten

Knowing that hybrid pricing is the default does not tell you how to run it well. The most successful hybrid structure uses a fixed subscription to anchor the customer relationship and a usage component to capture value as consumption grows. Companies that inverted this — leading with pure usage — reported more difficulty with forecasting, renewals, and contract negotiations. Leaders also made pricing legible to customers with usage estimators, monthly dashboards, commit-based discounts, and usage caps that prevent bill shock, and they designed pricing within the constraints of the quote-to-cash stack they actually had rather than adopting models their billing systems could not support. An AI-powered SaaS product leader described the base-plus-usage model in practice: “Customers pay a base subscription for core access, and then they incur additional costs based on usage, like the number of AI interactions or tickets. It lets customers start small with a predictable cost and then scale as their usage grows.” Where systems fall short, the strain is immediate — as one AI-enabled consulting revenue leader noted: “When you make a tailor-made, custom-made solution sale that is nonstandard … the billing process is not able to capture it.”

The topline statistic that 56% run hybrid GTM masks significant variation in how the motion operates. Three archetypes emerge, each with different economics and required capabilities. The right hybrid motion depends on product complexity, average deal size, and target segment — and companies often copy another company's balance without adapting it, ending up with a motion that fits neither their product nor their customer. A B2B SaaS GTM leader described the segmented pattern: “Smaller customers tend to move faster and more self-serve, while mid-market and enterprise usually go through a more structured sales process with demos, pilots.” Others walked self-serve back entirely — as one construction-tech GTM leader recounted: “We had PLG, but also sales led … We’ve gotten rid of that project-based pricing though, and now we’re a subscription-based price. The minimum price is $40,000. So now you need to go through our sales team in order to try the product.”

Hybrid GTM is now dominant in headcount and infrastructure, but revenue mix tells a more nuanced story. Among the 56% running hybrid GTM, 57% generate the majority of their customer volume through sales-led paths, and only 8% are majority self-service. Within hybrid companies, 13% have a roughly balanced split and ~22% are still figuring out their volume split — meaning 79% are predominantly sales-led or unsettled. Websites, demo requests, and free-trial paths look like self-service but route qualified prospects to sales for the actual transaction. A B2B SaaS GTM leader described exactly how the “self-service” surface feeds sales: “They come in inbound through our website, and they use CTAs — request a demo, request a contact, request a quote, request a free trial. Those then come into the business development team, go through qualification, and then get sent to the sales team.”

The ambition to run hybrid pricing and hybrid GTM has outpaced the systems that support it. Twenty-three percent of companies still manage hybrid pricing manually — spreadsheets, manual invoicing, and ad hoc reconciliation — and 21% run self-service and sales-led revenue on separate systems entirely. The cost shows up in delayed invoices, billing disputes, revenue leakage, and the time finance teams spend reconciling what should have been automated. Existing billing tools were designed for predictable seat counts, not usage that varies by customer and month. A B2B software product leader summed up the core problem: “The fragmentation between these systems and the billing and the products — they can’t all sync properly, perfectly in real time.”

Distributed revenue ownership and fragmented systems are not just governance issues — they translate into measurable operational costs that accumulate quietly across the year. The interview data surfaces four specific failure patterns that companies with fragmented revenue operations consistently describe. Each is small in isolation; together they represent meaningful revenue leakage and operational drag at scale. An IoT + SaaS product leader described the expansion cost: “The information loss happens later in the stage where … when sales is going back to upsell and cross sell, they don’t always know whether a customer’s had a bad experience.” A connectivity/telecom revenue leader described the billing cost: “One of my biggest friction points is when customers believe they are overcharged or incorrectly billed even when on the system it’s accurate … This case has required investigations across multiple systems and often manual reviews.”