"SaaSpocalypse": Why Replacing SaaS with AI Code Costs More Than It Appears

Analysts at TNW warn company executives: before replacing corporate SaaS subscriptions with AI-generated code, it's necessary to evaluate the full total cost of ownership — not just the initial development costs.

Why the idea sounds tempting

Generative AI has made creating internal tools radically faster. What previously required weeks of developer work is now created in hours — sometimes without a single line written manually by a human. That's precisely why more and more organizations are considering abandoning paid subscriptions to Salesforce, Notion, Slack, Zendesk and similar products in favor of their own solutions.

This scenario has already earned the name "SaaSpocalypse" in the industry — a predicted apocalypse of the SaaS market, where AI tools will gradually displace ready-made products. The logic is clear: if a language model writes a CRM system in one working day, why pay hundreds of dollars a year for a ready-made solution?

What gets missed when calculating costs

TNW points out a fundamental error in typical calculations: organizations compare the cost of development with the price of a SaaS subscription — and at this stage, their own solution almost always looks more profitable. The problem is that development is only the beginning of costs, not their main part.

The full cost of ownership of an internal tool includes:

• Regular updates for changes in business processes
• Security patches and vulnerability fixes as they emerge
• Employee support and documentation maintenance
• Integrations with new external systems as the business grows
• Developer work time that at this moment is not spent on the core product

In SaaS companies with thousands of clients, dedicated teams handle these tasks on an ongoing basis. Bringing functionality in-house means that all the same tasks are transferred to engineers who have other priorities — and other KPIs.

The right question for executives

The main thesis of the article: the question isn't whether a company can build a tool — today this is accessible to virtually any team. The question is whether it has the resources and sustainability to maintain, protect and develop it over several years.

"The key question is not whether an organization can build a tool, but

whether it has the resources and sustainability to support, protect and continuously develop it."

For large technology companies with developed engineering culture, such resources often exist, and in such cases internal development is economically justified. For most organizations, however, whose engineers are focused on the core product, the transition to internal tools creates hidden debt — technical, operational and data security related.

What this means

"SaaSpocalypse" as a mass phenomenon is more of an exaggeration than a real trend. AI has indeed lowered the barrier for creating highly specialized tools where ready-made SaaS solutions poorly address the specifics of a particular business. For standard functions, however — CRM, helpdesk, project management — replacing proven SaaS with your own code is justified only when there's a team ready to take responsibility for support for several years ahead.