The pursuit of product-market fit is a rite of passage for every startup. While countless guides exist on how to achieve this holy grail, the emergence of artificial intelligence (AI) throws traditional playbooks into disarray.
“It’s a completely different ball game,” declares Ann Bordetsky, a partner at New Enterprise Associates, speaking to a captivated audience at TechCrunch Disrupt in San Francisco. AI’s breakneck pace of development renders established metrics and strategies obsolete. The technology itself is constantly evolving, leaving founders grappling with new challenges and questions.
Despite this volatile landscape, seasoned investors like Murali Joshi from Iconiq Capital offer guidance for navigating the complexities of product-market fit in the AI realm.
One key indicator to watch is “durability of spend.” AI adoption within organizations is still nascent; much spending is earmarked for experimentation rather than integrated solutions. The crucial shift, Joshi points out, comes when companies integrate AI tools into their core operations and move beyond experimental budgets. “Digging into that,” he emphasizes, “is super critical to ensure this is a tool…that’s here to stay.”
Familiar metrics like daily, weekly, and monthly active users still hold relevance in the AI space. But, Joshi underscores, startups need to dig deeper: “How frequently are your customers engaging with the product they’re paying for?”
Bordetsky echoes this sentiment, advocating for a blend of quantitative and qualitative data. While metrics can offer clues, conversations with customers often provide crucial context. In-depth interviews, particularly those with executive stakeholders, reveal how AI tools fit within an organization’s workflow and technological infrastructure. This granular understanding helps determine the product’s “stickiness” – its ability to become an integral part of a company’s operations.
Crucially, both investors emphasize that product-market fit in the dynamic world of AI isn’t a static destination but rather a continuous journey. “It’s learning to think about how you maybe start with a little bit of product market fit in your space, but then really strengthen that over time,” Bordetsky advises.
Navigating this fluid landscape demands constant adaptation and refinement. The AI startup that grasps the nuances of evolving customer needs and technological breakthroughs will be best positioned to achieve lasting success.
