For decades, manufacturers shoehorned unique, physical business operations into rigid off-the-shelf software. It used to make sense when building custom software took months of work and hundreds of thousands of dollars to complete.

That barrier is now gone. With AI, a custom tool can be prototyped in a couple weeks. You can get feedback in days. And you can tweak it to fit exactly how your business operates.

Instead of manually cross-referencing supplier invoices and purchase orders, you can create a purpose-built agent that reads the paperwork, validates the information, processes the 98% that match cleanly, and flags the 2% with anomalies for human review. That’s demonstrable enterprise ROI.

Legacy SaaS vendors like to push back with two objections: maintenance and security. Neither argument holds water anymore.

First, if AI can build custom tools, it can maintain them. AI agents can automate code monitoring, regression testing, and bug patching under human-in-the-loop review.

Second, enterprise SaaS isn’t impenetrable. Despite SOC 2 and ISO certifications, databases can still be breached. When you build your own tools, you can embed automated security gates directly into your pipelines to ensure self-hardening code.

While AI has collapsed the time and effort required for development, effective custom tools don’t happen on a whim. There’s up-front work required to ensure they drive real results: analyzing operational friction, structuring and normalizing data, and finding the right workflow to act as a pilot project. But the juice is worth the squeeze.

In a few years, the concept of paying recurring seat fees for off-the-shelf software will look archaic. Build what fits your operations and let the legacy SaaS vendors fight over the scraps of a dying model.

Matt Wursta, Wursta founder