Why Most Consumer AI Startups Struggle to Scale — And What Comes Next

Even three years after the generative AI boom began, one truth stands out: most AI startups still make their real money from businesses, not everyday consumers.

While tools like ChatGPT reached millions almost overnight, most consumer-focused AI apps haven’t managed to build lasting engagement or defensible growth. According to leading venture capitalists, the reason is simple — consumer AI is still too early.

The “Flashlight App” Problem in Consumer AI

At TechCrunch’s StrictlyVC event, Chi-Hua Chien, co-founder of Goodwater Capital, compared today’s consumer AI apps to flashlight apps in the early iPhone era.

They were:

• Exciting

• Useful

• Short-lived

Once Apple added a flashlight directly into iOS, those apps instantly became irrelevant.

Chien believes many consumer AI startups face the same risk today. Early tools for video, audio, and image generation looked promising. But as powerful platforms like OpenAI’s Sora and open-source models spread rapidly, entire startup categories vanished almost overnight.

Platforms are moving faster than startups can build moats.

Why AI Platforms Haven’t Stabilized Yet

According to Chien, AI hasn’t reached the level of platform stability that mobile achieved around 2009–2010 — the era that gave birth to companies like Uber and Airbnb.

Right now:

• Models improve rapidly

• Costs keep falling

• New competitors emerge constantly

This makes it extremely difficult for consumer AI startups to build durable, long-term products without being replaced by platform-level features.

That said, there are early signs of stabilization. Google’s Gemini reaching parity with ChatGPT suggests the AI ecosystem may finally be settling into clearer layers.

Consumer AI Is Still in Its “Awkward Teenage Phase”

Elizabeth Weil, founder of Scribble Ventures, describes today’s consumer AI moment as an “awkward teenage phase.”

• The technology is powerful

• The use cases are unclear

• User habits aren’t fully formed

Consumers are curious, but not committed.

That’s why most AI revenue still comes from enterprise software, where productivity gains are immediate, measurable, and repeatable.

Will New Devices Unlock the Consumer AI Boom?

A key question remains: Is the smartphone the wrong interface for consumer AI?

Chien argues smartphones aren’t ambient enough. They capture only a small fraction of what users see, hear, or do — limiting AI’s full potential.

Weil agrees. She believes we won’t still be building AI-first experiences primarily for smartphones five years from now.

This has triggered a race to build the next personal computing device, including:

• Rumored screenless AI devices from OpenAI and Jony Ive

• Meta’s Ray-Ban smart glasses with gesture controls

• AI pins, pendants, rings, and wearables from startups

So far, results have been mixed — and often disappointing.

Not Every Consumer AI Breakthrough Needs New Hardware

Despite the device race, not all successful consumer AI products will require new hardware.

Some ideas that could still thrive on smartphones include:

• A deeply personalized AI financial advisor

• An always-on AI tutor tailored to each learner

• AI assistants that continuously adapt to user behavior

If these tools deliver long-term value, consumers may build habits around them, even without a new device.

Why AI-Powered Social Networks Face Skepticism

Both Weil and Chien are cautious about AI-first social networks, especially those filled with bots interacting with user content.

Chien summed it up perfectly:

“It turns social into a single-player game.”

Social platforms work because people know real humans are on the other side. Replace that human connection with AI bots, and the core value of social media starts to collapse.

The Bottom Line

Consumer AI isn’t failing — it’s still growing up.

• The technology arrived fast

• Platforms are still shifting

• Killer consumer use cases haven’t fully emerged

Just like mobile computing before it, AI likely needs a few more years of stabilization before the next wave of breakout consumer startups appears.

And when they do, they probably won’t look like the AI apps we see today.