There is no shortage of use cases or customer demand for generative AI. Users are eager for AI to simplify their jobs and improve their productivity, which is why they are flocking to these applications (despite their lack of natural distribution channels).
But will people continue to use them? Not really. The chart below compares first month mobile app retention rates for AI-led apps vs. incumbent companies.
User engagement is also not as good as it could be. Some hungary mobile database of the best consumer companies have 60-65% DAUMAU; WhatsApp’s is 85%. In comparison, the median for generative AI apps is 14% (notable exceptions being Character and the “AI Companion” category). This means that users are not yet finding enough value in generative AI products to use them on a daily basis.
In short, the biggest problem with generative AI isn’t finding use cases, demand, or avenues for diffusion, but proving its value . As our colleague David Cahn writes: “The $200 billion question is: What are you going to do with all this infrastructure? How will it change people’s lives?” The path to building a lasting business will require solving the retention problem and generating deep enough value for customers that they become daily active users.
We shouldn’t be disappointed. Generative AI is still in its “awkward adolescence.” We can see moments of brilliance, and when products fail to meet expectations, the failures are usually reliable, repeatable, and fixable. Our work is very clearly defined.