The emergence of powerful AI models has fueled a growing narrative that traditional software companies are on the verge of collapse in a disastrous “SaaSpocalypse.” But treating all SaaS businesses as commoditized code bases ignores the reality that many platforms run the workflows, transactions and networks that entire industries depend on.
Investors should start evaluating application software companies through a different lens — or risk mispricing and walking away from some of the most durable assets in enterprise technology.
The conclusion that AI will broadly eliminate SaaS misunderstands how most application software actually works, particularly vertical software focused on specific industries and business models.
The value of many vertical platforms does not lie in the code itself, but in the operational systems they facilitate within the complex ecosystems of various industries. These workflows include payments flowing between suppliers and distributors, compliance processes embedded in regulated industries and logistics networks connecting millions of businesses in a marketplace.
These platforms often sit at the center of the day-to-day operations of entire companies, organizing the set of daily tasks for their employees and enabling management oversight over global footprints.
Part of the confusion within the market narrative about the destruction of software stems from timing. The technology industry is currently experiencing two overlapping shifts.
First, many industries are normalizing after stimulus-driven boom years, when software companies enjoyed extraordinary growth and traded at valuations that extrapolated COVID-era growth rates as if they would occur indefinitely. But as interest rates rose and enterprise technology budgets tightened, growth slowed and valuations compressed across the sector.
The second shift was separate and wrongly conflated with the valuation drop. The rapid emergence of generative AI tools that can accelerate software development and automate certain knowledge tasks led some investors to conclude AI’s emergence caused the SaaS growth slowdown.
The most vocal AGI maximalists indeed think that software will become infinitely replicable and each company will develop its own tools to utilize internally. But the fact that the biggest AI cheerleaders think it (or wish it) doesn’t make it so.
Many industries’ primary vertical software platforms do not simply provide standalone features. Instead, they act as the platforms that coordinate the activities of thousands of participants across a complex network, both external buyers and sellers and internal employees within organizations.
Put simply, vertical software platforms organize how businesses operate. Without them, entire essential industries like retail, supply chain and energy would devolve into chaos. The requirement of industry verticals to synchronize the actions of various constituents makes the AGI-eats-SaaS vision for the future — millions of unique, non-interoperable company-developed software platforms — hard to grasp.
The challenge of reliably integrating and synchronizing divergent software systems has been the core inhibitor to growing vertical software applications over the past 20 years. Lowering the cost of coding does not make this process any easier or replace existing providers.
While AI can produce working code for any type of software, it certainly will be challenged to replicate decades of proprietary real-world integration that vertical platforms have built.
That said, AI certainly represents a compelling opportunity to expand the value of existing vertical software applications. For example, when AI agents eventually begin transacting on behalf of businesses, they will still need to operate through an existing digital substrate—and in most industries, that substrate will be the vertical platform already in place.
Artificial intelligence will undoubtedly reshape parts of the software landscape. AI may weaken some traditional pricing models. Many SaaS companies historically priced their products based on the number of users or seats within a customer organization, and as automation reduces headcount, those seat-based models may come under pressure.
That doesn’t necessarily imply shrinking software revenue or margins. Particularly as AI gains autonomy, pricing structures will likely move toward usage, transactions or outcomes. Revenue models will be based on the value those systems deliver, as many already do.
Investors previously viewed software as a high-growth, high-multiple business model that could generate venture-style returns. But as the industry matures, the next phase will reward investors with a different mindset—one focused on operational improvement, disciplined capital allocation and long-term platform building.
Investors and companies experienced in consolidating fragmented industries should be well-positioned to pursue this kind of strategy. By integrating complementary software assets into broader vertical platforms, growing both scale and profits is possible.
That makes AI more of an enabling technology than an engine of disruption for the right kind of vertical SaaS platform. The opportunity for investors lies in recognizing the difference between fragile software tools and durable industry infrastructure.
Rather than signaling the end of the sector, the current moment may represent the beginning of a new phase in which disciplined companies and investors can acquire and consolidate durable SaaS businesses while the market is distracted by the idea of a SaaSpocalypse.
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