The generative AI boom may have created a startup every minute, but according to Darren Mowry, many of those companies are now facing a reality check.

Mowry — who leads Google’s global startup organization across Cloud, DeepMind, and Alphabet — says startups built as simple “LLM wrappers” are in a risky position. These companies typically wrap existing large language models like OpenAI’s GPT, Anthropic’s Claude, or Google’s Gemini with a user interface or narrow feature set.

“If you’re really just counting on the back-end model to do all the work and you’re almost white-labeling that model, the industry doesn’t have a lot of patience for that anymore,” Mowry said.

Startups that layer only thin intellectual property on top of models like Gemini or GPT-5 may struggle to stand out. Instead, Mowry argues that companies need deep, defensible moats — either strong horizontal differentiation or highly specialized vertical solutions.

Examples of more defensible AI wrappers include Cursor, a GPT-powered coding assistant, and Harvey AI, which focuses on legal workflows. These companies embed domain expertise and workflow integration rather than relying solely on the underlying model.

The message is clear: simply putting a UI on top of a powerful foundation model is no longer enough to build a sustainable AI business.