In a recent TechCrunch feature, Lotan Levkowitz shares his perspective on where value is emerging in the AI landscape – beyond models and applications.
Is the AI application layer still open for new winners?
Despite U.S. dominance in large AI models, the race for the application layer remains wide open. European and Israeli startups are gaining ground, with emerging category leaders across industries. Investors continue to compete for opportunities in this space, even as questions around defensibility persist.
Where is the market focusing today – and what’s being overlooked?
Much of the market is concentrated on models, compute, and applications. However, Levkowitz points to a different layer that is still underappreciated.
“We see that most of the market today is chasing models, compute, and applications… and we think that data is undervalued at the moment.”
Why is data becoming a moat?
According to Levkowitz, companies that build around proprietary data and strong data flywheels can create more durable and valuable businesses.
“We strongly believe that companies focused on proprietary data and data flywheels are indeed very lucrative.”
As the AI stack matures, differentiation may increasingly come not just from the models or interfaces, but from the unique data assets companies can build and compound over time.
What is the broader insight for founders and investors?
The opportunity in AI is not limited to a binary choice between models and applications. A third layer – data – may define the next generation of category leaders.
Read the full article here on TechCrunch.
