According to a former vice president of Facebook, some of the hottest AI companies are expanding with “good instincts and good vibes” without many data foundations.
Julie Zhuo, former design vp for Facebook who co-founded AI Analytics startup Sundial, said many startups riding the AI boom have grown at such a furious pace that they don't have time to build the right data infrastructure.
“We see companies that are growing insanely, but they're still around 10 or 2,” she said.
“They have hundreds of millions of ARRs and hundreds of millions of users. You know you don't actually have all of that infrastructure.
Traditionally, businesses have not attacked 100 million users overnight. Due to slow growth, the team was given years to build a logging system, hire a data team, and develop “observability.” This is the ability to understand what actually drives users' behaviour and revenue, Zhuo said.
However, Zhuo warned that growth will not last forever. When the curves are flattened, these startups “scramble” to answer basic questions like why users churn, why they characterize people's values, and what levers actually drive business, she said.
“At that point, that's usually when people start investing tons in data,” she added. “Data helps us understand what's actually going on.”
Zhuo also said it is important to rethink how success in the AI era is measured, especially given the speed at which some companies are growing.
Products built around chatbots and conversational interfaces require new analytical methods. Instead of counting clicks or page views, she said, “we probably need to use LLM or machine learning models to use user intent in the bucket.”
Zhuo did not respond to requests for comment from Business Insider.
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AI companies boom
The fierce pace described by Zhuo reflects wider trends across the industry.
AI startups have raised record amounts and are surged in valuations, with over $35 billion raised in 2024, Business Insider reported last year.
Many investors are concerned that the AI market may be overheating and there is a risk of relating to the 2000 dot-com bubble burst. Some people wonder whether large-scale language models are actually strong enough to develop tight tensions over the years. Large spending by some tech companies is not rewarded. And some are worried that less experienced investors are getting caught up in the hype.
Openai CEO Sam Altman last month said last month that small AI startups are “incomprehensible” and “not reasonable” are getting funding with high ratings.
“Are we at a stage where the entire investor is overly excited about AI? My opinion is yes,” he told reporters. “Is AI the most important thing that will happen for a very long time? My opinion is yes too.”
