VCs discuss why most consumer AI startups still lack staying power

Even three years after the generative AI boom started, most AI startups are still making money by selling to businesses, not individual consumers.

Although consumers quickly adopted general-purpose LLMs like ChatGPT, most specialized consumer GenAI applications have yet to resonate.

“A lot of early AI applications around video, audio, and photo were super cool,” said Chi-Hua Chien, co-founder and managing partner at Goodwater Capital, onstage at TechCrunch’s StrictlyVC event in early December. “But then Sora and Nano Banana came out, and the Chinese open sourced their video models. And so, a lot of those opportunities disappeared.”

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

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

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

We could be seeing inklings of that stabilization with Google’s Gemini reaching technological parity with ChatGPT, Chien said.

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 being in an “awkward teenage middle ground.”

What will it take for consumer AI startups to grow up? Possibly a new device beyond the smartphone.

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

Weil agreed that a smartphone may be too limiting for reimagining consumer AI products in large part because it is not ambient. “I don’t think we’re going to be building for this in five years,” she said, indicating her iPhone as she showed it to the audience.

Startups and incumbent tech companies have been racing to build a new personal device that can supplant smartphones.

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

However, not every AI consumer product will be dependent on a new device. Chien suggested that one such offering could be a personal AI financial adviser customized to the user’s specific needs. Similarly, Weil anticipates that a personalized, “always-on” tutor will become ubiquitous, with its specialized tutelage delivered directly from a smartphone.

Though excited by AI’s potential, Weil and Chien expressed skepticism about the emergence of several, still-stealthy AI-powered social network startups. Chien said these companies are building networks where thousands of AI bots are interacting with the user’s content.

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