Q&A with Notion CEO Ivan Zhao on Notion becoming the “AI workspace that works for you”, being profitable, B2B vs. B2C, usage-based pricing for AI, and more
Casey Newton / The Verge : Bluesky: @caseynewton , @nickstatt , and @reckless . X: @notionhq Bluesky: Casey Newton / @caseynewton : For Decoder this week, I talked with Notion CEO Ivan Zhao about what LLMs have in common with beer www.theverge.com/decoder-podc... [image] Nick Statt / @nickstatt : Very fun episode of Decoder up today with Notion CEO Ivan Zhao, as part of @caseynewton.bsky.social's ongoing productivity series we're running this month. www.theverge.com/decoder-podc... Nilay Patel / @reckless : I knew before I even asked @caseynewton.bsky.social to guest host Decoder that he'd want to interview Notion CEO Ivan Zhao. Literally a dream episode! www.theverge.com/decoder-podc... X: @notionhq : “Better tools lead to better thinking” 💡 @Ivanhzhao joins @CaseyNewton on @DecoderPod to chat how Notion is reimagining productivity tools for the future workspace. Tune in to learn about: ∙ The importance of designing tools that match our natural thinking process ∙ The role of AI as a thought partner ∙ Notion's vision for the future of collaborative work
Context & Ripple Effects
Notion’s 2021 funding round valued the company at $10B; this interview shifts the focus from fundraising to operating posture, with Zhao discussing profitability and the trade-offs of selling AI across business and consumer markets. The earlier $275M financing provides the backdrop for that change in emphasis.
The conversation also precedes later coverage of Notion’s planned custom AI agents, suggesting that its “AI workspace” framing was an early articulation of a product direction that would move from assistance toward work performed inside the workspace.
First-order effects
- Notion presents profitability as part of its AI strategy, giving customers and prospective buyers a signal that its workspace business is not being framed solely around growth or model-driven experimentation.
- The company puts AI monetization—including the possibility of usage-based pricing—alongside its B2B-versus-B2C positioning, making pricing architecture a central product and go-to-market question rather than a back-office detail.
Second-order effects
- Workspace rivals face pressure to explain both how AI fits into existing collaboration products and how its costs will be recovered: bundled subscriptions, consumption charges, and segmented business plans become competing approaches.
- For enterprise buyers, an AI workspace’s value proposition increasingly depends on whether automation is embedded in the documents and databases where work already occurs, rather than offered as a separate chat interface.
Third-order effects
- If Notion and peers can make AI features reliably useful within daily workflows, the category may consolidate around systems of record that also execute parts of the work—an evolution later reflected in Notion’s custom-agent plans.
- Usage-based AI pricing could make software spending less predictable than seat-based SaaS, pushing vendors to tie charges more clearly to completed tasks or measurable workflow value; whether customers accept that shift remains unresolved.
The trend: Collaborative software is evolving from a place where teams organize work into an AI-native work surface that can increasingly participate in completing it.