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How should AI startups assess product-market fit?

Nigar Sultanli
12 November 2025 11:53
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How should AI startups assess product-market fit?

Even though AI startups make all kinds of innovative promises, they have long faced the traditional question: how can they know whether they have truly achieved Product-Market Fit (PMF)?

Although PMF has been studied for years, artificial intelligence is fundamentally changing the traditional rules and business principles in this area. At TechCrunch Disrupt in San Francisco, Ann Bordetsky, partner at New Enterprise Associates, stated, “This is completely different from all the old strategies we were taught in the tech world. This is an entirely different game.”

The main reason is the extreme speed of change in the AI world. Bordetsky explains, “The technology itself is not static,” meaning an approach that was relevant yesterday can become outdated today. Nevertheless, there are new ways for startup founders to assess whether they have achieved PMF.

Murali Joshi, partner at Iconiq, highlights one of the most important metrics to track: spending persistence. Many companies have not fully adopted AI yet and spend much of their budget on experiments rather than full integration. Joshi notes, “We are seeing more and more companies transition from experimental budgets to main CXO budgets. It’s important to dig into this to understand whether your product is a temporary trial or a lasting tool.”

Joshi also recommends tracking classic engagement metrics such as DAU, WAU, and MAU — daily, weekly, and monthly active users. “How frequently are your customers interacting with a product they pay for?”

Bordetsky agrees and adds that qualitative data (direct conversations and interviews with customers) help explain the reasons behind the numbers. Sometimes metrics may indicate that a customer isn’t leaving the product, but the true reasons can only be understood through direct discussions.

Joshi also suggests asking company leaders, “Where does this tool sit in your tech stack?” Startups should think about how to make their product more “sticky” in core business processes.

Finally, Bordetsky emphasizes that AI startups should view PMF not as a one-time achievement but as a continuous process. “Product-market fit is not an event that happens at a specific point in time. It starts by occupying a small space in the market and learning over time how to strengthen that position.”

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