Generative Product–Market Fit

Broadly speaking, latest surge of AI-driven products can be grouped into two categories.

The first includes AI features integrated into a broader service, supplementing its existing value. For instance, consider Box enhancing its platform with natural language search, Zoom introducing transcription services, or Notion integrating an AI assistant to facilitate content creation. Here, even without the AI element, these products would still function.

The second category represents entirely new products, with AI serving as the cornerstone. Without it, these products cease to exist. ChatGPT and Playground AI, an online AI image creator, are examples.

This stands in contrast to the 2015’s influx of natural language processing related products, which largely remained at the tech demo stage. But I’ve noticed a tendency to overstate the product-market fit of Generative AI because of the first category of products. Many argue that AI’s product-market fit is clearer than, say, that of cryptocurrency, given the surge in companies adopting LLMs or Stable Diffusion. I find this argument superficial. While it’s true that AI is increasingly incorporated into every service, often even when it’s not necessarily that beneficial, it’s rarely the fundamental component.

In my opinion, we’re nowhere near a consensus on product-market fit of AI products creating novel value propositions or business models. They’re in the nascent stages, and it’s unclear whether their current business models can survive. I anticipate seeing as many rise and fall in the fully-AI companies as we’ve observed in the cryptocurrency realm. (And much like cryptocurrency, many of the current winners appear to be infrastructure companies.)

This is why experiments like Intercom’s Fin are particularly intriguing. Fin is an AI-powered customer service bot. At first glance, it seems to complement Intercom’s traditional value proposition but it proposes an entirely new business model. While Intercom operates on a per-seat SaaS model, Fin’s pricing is based on usage: customers pay 99 cents per resolved conversation. This suggests that, should Fin prove successful, Intercom is prepared to cannibalize its non-AI SaaS operations believing that the new model will become a better business.

It’s a riskier venture than adding another text summarization feature to an existing app.