The SaaSpocalypse: AI Just Asked a Simple Question: Why Pay for SaaS?
SaaS isn’t dying.
It’s being questioned.
For years, software traded on a simple promise: recurring revenue, high switching costs, and deeply embedded workflows meant durability. That durability justified premium multiples. Investors weren’t just paying for growth—they were paying for certainty. AI is now challenging that certainty. Not because companies are suddenly losing customers, but because the value of the software itself is being reassessed.
AI is quietly compressing what used to be scarce. Capabilities that once required full platforms—customer support systems, content creation tools, analytics layers—can now be replicated by models sitting on top of lighter infrastructure. What used to be a product is starting to look more like a feature.
At the same time, switching costs are weakening at the edges. AI reduces friction. It helps rebuild workflows faster, replicate processes more easily, and lowers the dependency on rigid systems that once felt irreplaceable.
That doesn’t eliminate moats. But it changes how wide they really are. And once that doubt enters the system, pricing power comes into question. If the outcome can be achieved differently, and potentially cheaper, then the premium attached to traditional SaaS models becomes harder to defend.
Case Study — ServiceNow
ServiceNow built its position by owning enterprise workflows. The deeper it integrated into IT, HR, and operations, the harder it became to replace. That embedded position created one of the strongest durability arguments in software.
But automation is evolving. What was once rule-based and structured is becoming dynamic and model-driven. AI agents can now execute workflows in ways that don’t require the same rigid architecture.
ServiceNow is still critical infrastructure for many enterprises. That hasn’t changed. What has changed is the assumption that its dominance is untouchable. The business can continue to grow, but the multiple was built on a level of control that is now being challenged.
Case Study — Adobe
Adobe faces a similar shift from a different angle. Its strength has always been creative lock-in. Professionals learned the tools, built workflows around them, and stayed within the ecosystem.
AI changes that dynamic. Creation is moving from execution to instruction. The barrier is no longer technical skill inside a platform, but the ability to describe the desired outcome. That lowers the entry point significantly.
Adobe is adapting quickly, embedding AI across its products. But the question has shifted. It’s no longer whether Adobe participates in growth—it’s how much of the creative process still requires Adobe at all.
What the Market Is Actually Pricing
This isn’t about collapsing demand. It’s about declining certainty. Revenue can still grow. Adoption can still expand. But the confidence around long-term margins, pricing power, and control is weaker than it was before.
Markets don’t wait for deterioration. They move when the probability of change increases.
That’s what repricing looks like.
The Real Divide
The line forming underneath the surface is becoming clearer. Some companies will remain central to the workflow. They will integrate AI into systems that are still difficult to replace, still deeply embedded, still necessary. Others will drift toward the edges—offering capabilities that can be replicated, abstracted, or bypassed entirely.
The difference isn’t AI adoption. It’s whether the company still owns the outcome.
The real question remains if AI can deliver the same outcome…why pay for the software in its current form?
This is not a collapse in SaaS. It’s a repricing of certainty.
The model still works. The demand is still there. But the market is no longer willing to pay for dominance that might not hold. SaaS isn’t being replaced. It’s being forced to prove its value again.