SaaS Isn’t Dead: AI Is Changing When It Makes Sense To Build Your Own Software

Irina Shymko | CEO at Langate EMEA | Introducing innovations and transforming business in Europe/America | Lecturer, mentor, advisor.

​For years, the software decision for most small and midsize businesses was straightforward: buy, don’t build. The economics favored SaaS. Building a custom system meant assembling developers, business analysts, QA engineers and other specialists, then investing months of work before knowing whether the product would deliver enough value. Paying a subscription for an existing platform was the rational alternative.

The compromise was that businesses had to adapt their processes to software designed for thousands of other companies. The important shift is not that AI can generate code faster. It is that the cost of turning a well-defined business process into working software is falling. For businesses with specialized workflows, this changes what’s worth building and how they invest in technology.

Look for the workflow, not the product.

A common response to an operational problem is to search for better software. Consider a company where an employee receives a customer request, checks data in a CRM, copies information into another system, calculates it in Excel, requests approval, updates the CRM and generates a document.

The company might blame the CRM. But the CRM may not be the problem. The expensive part is the human coordination happening between systems. Instead of replacing an entire platform, an AI-assisted team could build a lightweight operational layer that retrieves the necessary data through APIs, applies business rules, triggers human approval for defined exceptions and updates the relevant systems. That is a much smaller engineering problem.

A 20-minute manual process performed twice a month probably does not justify development. The same process performed hundreds of times per week may. Technology investment should be compared with the cost of the current process, not with zero.