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Generative Product–Market Fit

The product-market fit of AI remains uncertain, especially for those proposing new business models.

2 min read
Generative Product–Market Fit
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Before Growth is a weekly column about startups and their builders prior to 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.


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