These 2 types of AI start-ups are at risk
What's the story
Darren Mowry, who leads Google's global start-up organization across Cloud, DeepMind, and Alphabet, has warned that two types of artificial intelligence (AI) start-ups could struggle to survive. These are LLM wrappers and AI aggregators. He said these business models have their "check engine light" on as the generative AI boom begins to stabilize.
Business models
What are LLM wrappers and AI aggregators?
LLM wrappers are start-ups that use existing large language models (LLMs) like Claude, GPT, or Gemini with a product or user experience layer to solve specific problems. For instance, an AI-powered platform helping students study could be an example of this model. On the other hand, AI aggregators bring together multiple LLMs into one interface or API layer, to route queries across models and give users access to various options.
Market advice
'Industry doesn't have a lot of patience'
Mowry emphasized that start-ups can't just rely on the back-end model to do all the work anymore. He said, "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." He stressed on having "deep, wide moats" either horizontally differentiated or something really specific to a vertical market for a start-up to progress and grow.
Growth hurdles
Stay away from the aggregator business, warns Mowry
Mowry also warned incoming start-ups to "stay out of the aggregator business," as these companies aren't seeing much growth or progression. He said users want "some intellectual property built in" to ensure they're routed to the right model at the right time based on their needs. This is not due to behind-the-scenes compute or access constraints, but rather a demand for more sophisticated solutions from AI aggregators.
Industry comparison
Comparison to early cloud computing start-up struggles
Mowry compared the current state of AI aggregators to early cloud computing start-ups in the late 2000s/early 2010s. These companies were squeezed out when Amazon started building its own enterprise tools and customers learned how to manage cloud services themselves. The only ones who survived were those that added real services like security, migration, or DevOps consulting - a lesson for today's AI aggregators facing similar margin pressure, as model providers expand into enterprise features themselves.
Future trends
Other areas of opportunity for venture investment
Despite the challenges for some AI start-ups, Mowry is optimistic about vibe coding and developer platforms. He noted a record-breaking year in 2025 with start-ups like Replit, Lovable, and Cursor attracting major investments and customer traction. Beyond AI, he also sees potential in biotech and climate tech due to venture investment and the "incredible amounts of data" available for creating real value.