Startup ARR is less secure than ever, new research shows

Yet, for the first time ever, enterprise revenue remains insecure, even after a startup’s AI product graduates out of a pilot phase and gets adopted by a company.

Part of the issue is that many AI startups haven’t fully landed on a good way to price their AI wares for enterprises. New research from VC firm Andreessen Horowitz that surveyed 50 technical AI buyers, found that more than half of them want AI fees tied to the work produced or other outcomes, rather than to usage like the number of tokens consumed.

Charging for usage like tokens is basically a SaaS-era business model. Once an enterprise knows it needs email, or HR software, or cloud storage, it’s merely a matter of how many employees or how much data it must pay for.

For AI, pricing “around the recognizable work” is what helps the startup prove its worth to the customer. When the fees revolve around, say, how many reports are processed, or tickets closed, or leads generated, this makes the product “economically valuable to both sides,” writes a16z partners Tugce Erten and Sarah Wang.

All of this means that AI has potentially ushered in a new era of enterprise experimentation. That opens doors to startups — enterprises are more willing to try their tech — but it also means an enterprise contract no longer secures long-term revenue. When or if enterprises will revert to their long-term buying habits remains to be seen.