Why AI Startups Need to Focus on Distribution Before Disruption

The article argues that AI startups often focus too much on technical disruption and not enough on distribution. It explains why distribution is crucial for AI products and how startups can build trust and mindshare with their audience.

Details

The article argues that the familiar startup story of building something technically impressive and then expecting adoption to follow doesn't work in the AI era. Today, technical capability is abundant, but attention is scarce. AI products often look similar from the outside, so adoption is driven more by where people discover the product, how often they encounter it, and how much they trust the source, rather than technical depth. Disruption answers what's new, better, and different, but distribution answers where people spend time, how they make decisions, and what triggers action. Most AI startups focus too much on the first set of questions and ignore the second, which is a fatal imbalance. Real distribution is about being present at the moment of need, embedding into existing workflows, integrating with tools people already use, and becoming a trusted voice, not just a tool. The startups that win are the ones that shape the conversation early, educate their audience, and define the problem before selling the solution. Distribution-led companies build familiarity, trust, mindshare, and long-term relevance, while disruption-only companies often end up chasing constant feature upgrades and struggling with retention.