While AI expands software's capabilities, vendors may not capture the value. Companies could use AI to build solutions in-house more cheaply. Furthermore, traditional "per-seat" pricing models are undermined when AI reduces the number of employees required, potentially shrinking revenue even as the software delivers more value.

Enterprise sales for SaaS companies are becoming harder because AI has dramatically lowered the cost and time required for customers to build solutions in-house. This gives customers a credible alternative during renewal negotiations, eroding the vendor's pricing power and leverage.

Enterprises no longer need to buy expensive SaaS products for tasks like customer feedback. They can now spin up custom AI agents internally, making it harder for SaaS companies to acquire new customers and leading to higher-than-modeled churn. This poses a fundamental threat to the SaaS business model.

A new trend sees AI-native companies leveraging their own AI-assisted developers ('vibe coders') to create internal software that replaces their subscriptions to commercial SaaS products. This represents a significant threat to the traditional SaaS business model, as companies opt to build rather than buy simple tools.

Companies are now rejecting expensive SaaS contracts because their internal teams can build equivalent custom solutions in days using AI coding tools. This trend signals a fundamental threat to the traditional SaaS business model, as the 'build vs. buy' calculation has dramatically shifted.

For decades, buying generalized SaaS was more efficient than building custom software. AI coding agents reverse this. Now, companies can build hyper-specific, more effective tools internally for less cost than a bloated SaaS subscription, because they only need to solve their unique problem.

The mere existence of powerful AI development tools shifts negotiating power to enterprise software buyers. Even if they have no intention of replacing an incumbent SaaS vendor, procurement teams can now plausibly bluff about building an in-house alternative with AI, creating significant downward pressure on pricing and renewals.

The narrative that AI will kill SaaS is flawed. While anyone can now use AI to build custom tools, established companies retain value through brand and distribution. The real impact is deflationary: SaaS companies must lower prices to compete with the new "build-it-myself" alternative, compressing margins across the industry.

The ability for customers to build their own software features using AI agents directly threatens the traditional SaaS upsell model. During negotiations, customers can now credibly threaten to "roll their own" features instead of paying for higher-priced tiers, weakening the vendor's pricing power.