AI-native software companies retain customers at half the rate of traditional SaaS — but only below $250 a month

Two SaaS retention stories are running in parallel in 2026. The first is the familiar one: churn benchmarks tracked across thousands of subscription businesses, largely stable year over year. The second is new and much more dramatic: a measurable retention gap between AI-native software and traditional SaaS, sharp enough that a $250-a-month AI product retains customers like an enterprise SaaS company, while a $20-a-month one loses customers like a free trial. This page covers both — the baseline numbers and the AI-driven divergence — along with a credible counter-argument that the loudest "AI is killing SaaS" headlines may be describing a budget story, not a churn story.

The 2026 baseline: SaaS churn sits around 3.2%

Recurly's subscription-business network puts SaaS at a 3.22% average churn rate as of its July 2026 data — split between 2.16% voluntary churn (customers actively canceling) and 1.06% involuntary churn (failed payments and billing issues). That puts SaaS among the stickier verticals Recurly tracks:

That figure lines up closely with a separate synthesis of the 2025 Recurly Churn Report, which put average B2B SaaS churn at 3.5% — 2.6% voluntary and 0.8% involuntary — suggesting the baseline has held roughly steady year over year even as the AI-native story below has moved fast.

AI-native software is a different retention animal entirely

ChartMogul's 2025 retention analysis — which scraped and categorized roughly 3,500 software company websites into B2B SaaS (~2,700), B2C SaaS (~600), and AI-native (~200) companies with at least $250,000 in ARR — found a stark divergence. B2B SaaS companies posted an 82% median net revenue retention (NRR) in 2025; B2C SaaS came in far lower at 49% median NRR; and AI-native companies landed in between on NRR (48%) but with a much lower 40% median gross revenue retention (GRR) — meaning AI-native companies are both losing more revenue to cancellations and relying more heavily on expansion revenue from the customers who stay to offset it.

Price is the single biggest divider within AI-native retention

The starkest finding in ChartMogul's data isn't the AI-vs-SaaS gap overall — it's how much that gap depends on price point:

Above $250 a month, AI-native retention is essentially comparable to traditional B2B SaaS. Below $50 a month, it's a different business entirely — a 23% gross retention rate means more than three-quarters of customers who sign up don't stick around, a pattern more typical of a low-commitment trial product than a subscription business. ChartMogul also found retention improving through the year at the median — gross retention rose from 27% in January 2025 to 40% by September — but reads this as evidence of early adopters churning out and leaving a smaller, more committed base behind, rather than proof that AI-native retention is durably improving for every cohort.

Company maturity compounds the effect: more established, higher-ARR AI-native companies showed roughly 2x the gross retention and 2.5x the net retention of earlier-stage AI-native peers in the same analysis — a sign that the retention gap narrows considerably once a company has proven a durable use case and pricing model, but that a large share of the earliest AI products haven't gotten there yet.

Is this actually a churn story — or a budget story?

Not every account of 2026's turbulence in software stocks is a retention story. SaaStr founder Jason Lemkin has argued publicly that what's being called a "2026 SaaS crash" is better explained by budget reallocation than by customers churning to AI replacements: enterprise IT budgets grew only about 8% year over year in 2026, while AI budgets grew more than 100% over the same period — with declining SaaS stock prices (Lemkin cites a 22% drop in the IGV software index and an 11% drop for ServiceNow despite beating earnings) reflecting weak net-new customer growth and slowing expansion revenue rather than customers actively canceling and switching to an AI agent. Under this reading, seat-count compression — companies needing fewer employees, and therefore fewer software seats, even while keeping the software itself — explains more of the pressure on SaaS growth than churn does. The two accounts aren't necessarily in conflict: ChartMogul's data shows real, measurable churn concentrated specifically in cheap, early-stage AI-native products, while Lemkin's argument is about established SaaS incumbents, where the pressure looks more like starved growth than lost customers.

Methodology

Churn and retention figures on this page are drawn from publicly published research by subscription-billing and analytics platforms, cited individually below, current to their publication dates in 2025 and 2026. These figures reflect each provider's own customer or scraped-website data rather than a single unified industry census, and different providers use different underlying samples and time periods — which is why the Recurly and Vitally-cited figures, though close, aren't identical. ChartMogul's AI-native category was built by categorizing scraped company websites rather than a self-reported survey, and its report explicitly covers only companies with $250,000 or more in ARR. Commentary on the 'SaaS crash' narrative reflects one industry commentator's published opinion, presented alongside the retention data rather than as an independently verified conclusion.

References

1. Recurly. (2026, July). Churn Rate Benchmarks: SaaS, Media, Retail & More Industries. https://recurly.com/research/churn-rate-benchmarks/
2. ChartMogul. (2025). The SaaS Retention Report: The AI Churn Wave. https://chartmogul.com/reports/saas-retention-the-ai-churn-wave/
3. Vitally. (2025). B2B SaaS Churn Rate Benchmarks. https://www.vitally.io/post/saas-churn-benchmarks
4. SaaStr (Jason Lemkin). (2026). The 2026 SaaS Crash: It's Not What You Think. https://www.saastr.com/the-2026-saas-crash-its-not-what-you-think/