Overview
Benedict Evans argues that OpenAI lacks clear product-market fit despite impressive AI capabilities, with most users only engaging a few times per week. OpenAI’s advertising strategy represents an attempt to solve this engagement problem by offering expensive models to free users.
Key Arguments
- OpenAI doesn’t have clear product-market fit - the ‘capability gap’ between what models can do and what people actually do with them reveals fundamental engagement issues: Most users only engage with ChatGPT a couple times per week at most and can’t think of daily use cases, indicating the technology hasn’t meaningfully changed their lives
- OpenAI’s advertising strategy serves dual purposes - covering costs for non-paying users while attempting to deepen engagement through access to premium models: 90% or more of users don’t pay, so ads help subsidize their usage while potentially giving them access to more powerful (expensive) models that might increase their engagement
Implications
This suggests that AI companies may be overestimating consumer demand for their products. Even with breakthrough capabilities, the real challenge is creating daily habits and clear value propositions that justify regular use. OpenAI’s pivot to advertising indicates they’re still searching for sustainable business models that align with actual user behavior rather than theoretical potential.
Counterpoints
- Early adoption patterns don’t predict long-term success: Many transformative technologies initially had low engagement before finding their killer applications - the internet, smartphones, and social media all followed similar patterns
- Professional and enterprise usage may be different: While consumer engagement may be low, business users might have more consistent, high-value use cases that aren’t reflected in general user statistics