Why AI Isn’t Killing SaaS Yet
5/25/202640 min
Originally aired on MTS segment, Monetary Matters, Jack Farley and Max Wiethe speak with Ara Kharazian, Lead Economist at Ramp, about what real business spending data says about AI adoption, why the “SaaSpocalypse” narrative is overblown, and how companies are actually buying and deploying AI tools. They also discuss Anthropic overtaking OpenAI in Ramp’s AI Index, token-based pricing, AI productivity gains, and why many legacy software firms may be more resilient than people expect.
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Clips
Transcript preview
First 90 secondsAra Karazian· Guest0:00
This is one of the most dynamic markets we've seen, particularly for buying software, where month over month you will see large incumbents be replaced by the newcomers. Anthropic just did that with OpenAI, now the most popular model used by businesses according to Ramp data. Cursor did that with GitHub Copilot. My main take is that SaaSpocalypse as a pronouncement has come way too soon and is typically not informed by actual business behavior.
Jack Farley· Host0:26
We say SaaSpocalypse is not in the data.
Ara Karazian· Guest0:30
I'd say quantitatively, neither aspect of SaaSpocalypse is supported by actual business spend. Neither aspect as in it's going to change the way we buy it. Currently, it has not in any meaningful way, nor has it killed off at least the companies that are frequently mentioned.
Jack Farley· Host0:47
This episode originally aired on the MTS segment Monetary Matters. For the last two years, the dominant story in software has been that AI will wipe out SaaS companies, collapse seat-based pricing, and centralize everything around a handful of frontier model providers. But when you look at actual business spending data, that story becomes much harder to defend. Many of the fastest-growing AI companies are not model labs themselves, but the infrastructure, workflow, and application layers forming around them. At the same time, businesses are increasingly using multiple models, becoming more cost-conscious and experimenting with AI in ways that don't neatly fit the prevailing narrative