SaaS or Services-as-Software: Why AI Is a Tailwind for Software, Not an Apocalypse

ZDNet has published an analysis arguing that the so-called "SaaS apocalypse" driven by artificial intelligence is greatly exaggerated, and that AI is becoming a powerful tailwind for software companies rather than their undertaker. The piece offers five principles for adapting to the new software market model, Services-as-Software (SaS).

What is Services-as-Software

Services-as-Software (SaS) is a model in which AI agents do the work itself rather than merely helping a human do it. In classic SaaS (Software-as-a-Service), a company sells a tool, and the customer's employees produce the result: a CRM doesn't manage your deals for you, it only helps you manage them. Under SaS, the customer buys a finished service, such as legal analysis, request processing, or tech support, and an autonomous agent, not a human, does that work under the hood.

ZDNet calls this shift from "selling access" to "selling outcomes" the main change in the software market. Take a law firm: it used to buy document-handling software and put lawyers to work in it. Under SaS, an agent prepares the document itself, and the client pays for the finished result. This blurs the line between "software" and "service," and labor markets such as support and accounting turn into markets for software products.

Will AI kill the SaaS market

AI does not destroy software companies; it expands their market. That is the central thesis of the column. The ZDNet author argues that the fear of a "SaaS apocalypse" rests on a false premise: that neural networks will quickly displace off-the-shelf products. In practice, mature SaaS companies have what AI startups built from scratch lack: accumulated customer data, distribution channels, market trust, and deep integration into workflows.

Bare "AI wrappers" with no data of their own and no customer base are easy to copy and have no moat, whereas the real barrier, proprietary data and workflow integration, is something incumbent SaaS vendors already have. So by adding agents on top of a mature product, many of them raise their average deal size rather than lose it.

"AI is a huge tailwind for software companies," the ZDNet columnist writes.

What software companies should do

Software companies should stop competing on feature count and start competing on how much work their product does for the customer without the customer's involvement. ZDNet groups its five tips around that idea. The logic of the SaS model moves the point of value: what matters is not how many buttons the interface has, but how much routine the system handles on its own. Hence the typical steps in the transition: moving pricing to pay-per-outcome, embedding agents directly into the existing product, and turning accumulated data into an advantage that is hard to copy.

The practical upshot is to measure success by the volume of completed tasks, not by the number of licenses. A company that sells "outcomes" rather than "access" changes its metrics too: the number of subscribers gives way to the share of work done by agents and the retention of customers who care specifically about the result.

What this means

The debate is not about whether software will survive as an industry, but about who will capture the margin from automation: the makers of tools, or those who learn to sell the finished result. The takeaway for any SaaS team is practical: competitive advantage is shifting from a set of features to embedded AI agents that do the whole job, and the winners will be those who rebuild their product and pricing around this logic before their competitors do.