I’ve spent years building AI systems that reshape how professional work gets done. And the  thing I keep noticing is that the SaaSpocalypse debate is focused on the wrong layer. From  inside those systems, the distinction between where value is compounding and where it’s  eroding is already clear. 

The Claim Most Software Companies Don’t Want to Hear 

Much of enterprise software doesn’t have durable differentiation. It has a wrapper. 

The argument that AI agents threaten software built on workflow interfaces is essentially  correct. If an AI agent can perform the tasks an application was built to support, that  application becomes optional. And if AI can also write the interface software itself, then  the wrapper simply is not necessary. It is fungible and easily reproducible. 

The companies being repriced are not being repriced because of panic. They are being  repriced because their differentiation was always the interface: the interaction model,  the workflow sequence, the UI skin on top of someone else’s data. When the interface is  no longer a screen but a conversation, and multiple models can deliver that interaction,  the wrapper carries far less value. 

This applies specifically to the application layer, the part of software that manages how  users interact with information, not the information itself. The layer of information  interaction is commoditizing quickly. Organizations whose competitive position lives  there should be alarmed. We see this play out in real workflows, where the interface is  becoming more flexible while the underlying intelligence and data are doing more of the  work. 

What the Debate Gets Wrong 

The SaaSpocalypse narraLve oKen stops there, at the collapse of the wrapper, as if that is the  whole story. It is not. 

What AI is actually doing is shifting value downward through the stack, not destroying it.  The application layer is commoditizing. The intelligence layer is not. In fact, the agentic  capabilities of modern AI systems support a thesis that differentiation in that layer is 

growing and durable. The more complex the work agents are asked to do, the harder it  becomes to fake the underlying competence. 

As agents take on more complex, multi-step work, the gap between intelligence that can  be trusted and intelligence that merely sounds convincing widens. The stakes of getting it  wrong go up. So does the value of getting it right. 

In professional work, including legal research, tax analysis, clinical decisions, and financial  due diligence, humans will remain in the loop. Not because AI cannot draK the analysis or  produce the recommendaLon, but because accountability cannot be delegated. A  lawyer’s signature on a brief is sLll their signature. A tax advisor’s filing is sLll their filing.  

But the experience of reviewing AI output is not where the competitive game is played. Far  more value sits in two places that have nothing to do with the interface at all. 

The Two Layers That Actually Matter 

The first is the trustworthiness of the underlying intelligence. 

In professional contexts, accuracy is not a nice-to-have. A hallucinated case citation, an  incorrect tax precedent, a misread clinical guideline; these are not annoying errors. They  are failures of professional responsibility. General-purpose AI can generate plausible sounding output. Professional AI has to be accurate, grounded, and able to produce  outputs professionals can verify. 

That requires domain-specific training, grounding, and validation that most general purpose models do not have. And it requires systems that can stand behind the result,  not just generate it. The intelligence layer is not a commodity. It is not being disrupted. It  is becoming more important. 

The second is the knowledge and content grounding the work. 

This is where the real competitive advantage lives, and it is almost never mentioned in  SaaSpocalypse discussions. If trustworthy intelligence is the engine, authoritative domain  content is the fuel it runs on. And you cannot replicate it quickly or reliably from scratch. 

The value of a legal research platform has never been its search interface or its workflow  tools. It’s been the comprehensiveness and integrity of the underlying corpus: decades of  case law, statute interpretation, and regulatory guidance organized, verified, and  continuously maintained. When an AI agent conducts legal research, the quality of its  output is bounded by the quality of the knowledge it’s operating on. An agent grounded  in authoritative legal content produces fundamentally different work than one operating  on scraped public data. The same logic applies across every professional domain:  regulatory guidance in tax, validated clinical evidence in healthcare, verified transaction  history in finance.

The organizations that have spent decades assembling and maintaining that knowledge  infrastructure are not facing a SaaSpocalypse. They’re looking at a world where their content  becomes more valuable, not less, because AI agents need something authoritative to run on,  and it turns out that takes a very long time to build. 

The Question Leaders Should Actually Be Asking 

The question executives should be asking isn’t which applications to keep. It’s where the  knowledge actually lives in their software stack. From where I sit, inside systems built for high stakes professional use, that disLncLon is already clear. Investors are starLng to reflect it. The  recovery has not been uniform. Companies with deep proprietary data and domain-specific  knowledge infrastructure are beaer posiLoned than companies whose value is concentrated in  the interface alone. In this next phase, AI will start the work. But systems built on trusted data,  domain experLse, and verifiable intelligence will be the ones that stand behind it. 

The SaaSpocalypse is real. But what is dying is not soKware. It is the long-standing illusion that a  good interface was ever the same thing as real intelligence. 

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.