How do you actually calculate ROI when switching from fragmented AI licensing to a unified model?

I had to justify this same shift at my company. Here’s what actually worked: we built three ROI models in parallel. The first was pure cost—API spend today versus unified subscription. Second was operational overhead: time spent managing keys, billing, compliance across vendors. Third was velocity: how long does it take to spin up a new automation workflow end-to-end with our current fragmented setup versus a unified platform.

What surprised finance most was the second number. We found one person was effectively half-dedicated to contract management, access provisioning, and billing reconciliation. That’s a real cost hiding in operational overhead.

For the velocity piece, we ran a pilot where one team built the same workflows on both systems. Consolidated setup was about 35% faster because they didn’t have to learn multiple platforms and API documentation. That translates directly to ability to deliver more automations per quarter without hiring.

Latenode made this calculable for us because consolidating to their one subscription meant one billing process, centralized governance, and unified API documentation. We could actually measure the difference in team productivity.