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You are at:Home»AI»VCs discuss why most consumer AI startups still lack staying power
AI

VCs discuss why most consumer AI startups still lack staying power

techtost.comBy techtost.com16 December 202503 Mins Read
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Even three years after the AI ​​boom began, most AI startups are still making money by selling to businesses rather than individual consumers.

Although consumers have quickly adopted general-purpose LLMs such as ChatGPT, most specialized consumer GenAI applications have yet to catch on.

“A lot of early AI applications around video, audio and photos were really good,” Chi-Hua Chien, co-founder and managing partner of Goodwater Capital, said on stage at TechCrunch’s StrictlyVC event in early December. “But then Sora and Nano Banana came along, and the Chinese created the open-source video models. And so, a lot of those opportunities disappeared.”

Chien compares some of these apps to the simple lens, which was initially a popular third-party download after the iPhone launched in 2008, but quickly became integrated into iOS itself.

He argued that just as it took a few years for the smartphone platform to solidify before game-changing consumer applications emerged, AI platforms need a similar “stabilization” period for lasting consumer AI products to flourish.

“I think we’re on the cusp of the mobile equivalent of the 2009-2010 era,” Chien said. That period was the birth of massive mobile-first consumer businesses like Uber and Airbnb.

We could see signs of this stabilization with Google’s Gemini reaching technological parity with ChatGPT, Chien said.

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San Francisco
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13-15 October 2026

Elizabeth Weil, founder and partner at Scribble Ventures, echoed Chien’s sentiment about the early days of GenAI, describing the current state of consumer AI applications as an “awkward teenage middle ground.”

What will it take for consumer AI startups to scale? Probably a new device beyond the smartphone.

“It’s unlikely that a device that you pick up 500 times a day but sees only 3% to 5% of what you see is what ultimately introduces the use cases that take full advantage of AI,” Chien said.

Weil agreed that a smartphone might be too limiting to redefine consumer AI products largely because it’s not an environment. “I don’t think we’ll be building for this in five years,” she said, pointing to her iPhone as she showed it to the audience.

Startups and established tech companies alike are racing to build a new personal device that can replace smartphones.

OpenAI and former Apple design chief Jony Ive are working on a device rumored to be a pocket-sized “screenless” device. Meta’s Ray-Ban smart glasses are controlled by a wristband that detects subtle gestures. Meanwhile, a number of startups are trying, often with disappointing results, to introduce a pin, locket or ring that uses artificial intelligence in a different way than smartphones do.

However, not every consumer AI product will depend on a new device. Chien suggested that such an offering could be an artificial intelligence personal financial advisor tailored to the user’s specific needs. Likewise, Weil expects a personalized, “always-on” teacher to become ubiquitous, with expert tutelage delivered directly from a smartphone.

Although excited by the potential of AI, Weil and Chien expressed skepticism about the emergence of several, as-yet-hidden, AI-powered social networking startups. Chien said these companies are building networks where thousands of AI bots interact with user content.

“It’s turning social into a single-player game. I’m not sure it’s working,” he said. “The reason people enjoy social networking is the understanding that there are real people on the other side.”

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