SaaS Catch-22
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The SaaS Catch-22
Every SaaS company wants an AI story.
But to have a credible AI story, you need to show that people are using your AI product. To show people are using your AI product, you have to show margin erosion.
And nobody wants to show margin erosion because they’re afraid it will tank their stock.
This is the fundamental paradox of public (and private) SaaS in 2025.
Last weekend I listened to an interview with investor Gavin Baker, who gave some great perspective to this dilemma.
“Anybody can just look at the P&L of a SaaS company circa 2021 and 2022 and you see 80, 90% gross margins. And the nature of AI, because of scaling laws; ‘the bitter lesson’, they’re just more compute intensive. So their gross margins are structurally going to be lower.”
An eye-opening example of this was when Notion CEO Ivan Zhao told the WSJ that 10% of Notion profits go directly to the LLMs.
This is the new reality that application layer players need to live with.
The challenge is that public market analysts still judge SaaS companies by traditional margin expectations, creating a brutal tension between short-term financial metrics, and long-term product monetization decisions.
Baker fears most SaaS players are falling into the trap of short-term thinking:
“I worry that Application SaaS companies are trying to preserve their existing gross margin structures, because they believe that if their gross margins go down, their stocks will go down. It is definitionally impossible, given what we just discussed, to succeed in AI without gross margin pressure.”
The same dynamic appears to be playing out in the private markets as well.
David George, General Partner at a16z (and Gavin’s interviewer) noted that lower margins have become a credibility signal in their conversations with startups, calling it a “badge of honor” for these companies to have lower gross margins because it means people are actually using their AI products.
Both Baker and George agree that one of the key skills for modern SaaS leaders is to master the story around this shift, and Baker drew a direct parallel to the transition from on-prem to cloud as a playbook to follow.
“It used to be that companies were scared to go from on-premise to the cloud because margins were lower. Cloud margins are lower, but they’re still good. And Microsoft, they transitioned from on-premise, perpetual licenses with maintenance, to a cloud model and it was a pretty good stock for 10 years.”
The companies that survived cloud transitions didn’t hide from margin compression, they made the new economics legible to investors. The same playbook applies here.
George called out Figma as a company that already embraced this narrative, telling analysts that they’re going to aggressively distribute their AI tools, prepping them for margin erosion.
A few months back, Figma launched Make, its Lovable competitor, bundling it into Full seat access without raising prices. Then this past month, Figma introduced AI credits and MCP functionality, again, without raising the price of a full seat.
On the other side is Freshworks. In their last earnings call, Freshworks referenced AI revenue doubling YoY to $20M ARR and telegraphed a price increase, which went live last month. They ended up 5x’ing the price of their AI agent, Freddy.
While Figma is clearly optimizing for adoption, it seems Freshworks is moving further down the path to monetization. It’s unclear which is the right long-term move, but in the short term, it seems analysts prefer what Freshworks is doing.
Perhaps this suggests analysts are looking for a combination of a real AI product, proof of usage, and the willingness to monetize quickly after initial traction.
That said, these are just two examples, and many factors influence stock price. We’re still too early to understand price elasticity for these AI products, which will help inform the tradeoff between adoption and monetization downstream as well.
From Baker’s perspective, it’s okay if AI adoption outpaces margins for the time being:
“The big advantage these legacy application SaaS companies have, is they do have these really profitable existing businesses. And so they can run new AI products at breakeven, and catch up to the leaders.”
One thing that will help these companies tell a more compelling story is proof that AI adoption provides leverage. That could mean higher LTVs through improved retention, increased NRR, or expanded use cases that justify tighter margins. We’re still in the early days, but will be watching closely to see how these stories unfold.
PS. If you’re dealing with this firsthand, we’ve got an active thread in the PricingSaaS Community where other operators and pricing experts shared their approach.
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