For the past three years, AI has been the hottest ticket in tech. Billions in venture funding, explosive hype cycles, and a flood of new startups promising to “revolutionize” industries have created what feels like a modern-day gold rush. But behind the noise, a sobering reality is emerging: most AI startups are not built to last.
We are on the brink of AI’s first extinction event—a mass die-off of companies that raised fast, scaled hastily, and built on foundations too fragile to survive the coming storm. Here’s why.
1. The Infrastructure Problem: Building on Rented Land
Many AI startups don’t actually “own” their technology stack. Instead, they rely on third-party large language models (LLMs) and cloud infrastructure owned by giants like OpenAI, Anthropic, Google, and Amazon.
That creates two existential issues:
- No moat: If your product is just a thin UI layer on top of GPT, you’re one API call away from being replaced by the platform itself.
- Rising costs: Cloud compute and inference costs scale badly. For many startups, customer growth actually means losing more money.
When your landlord also happens to be your competitor, survival is not a long-term strategy.
2. The Funding Bubble: Too Much, Too Soon
VCs, eager not to miss the “next OpenAI,” have poured billions into AI companies with little more than a demo and a pitch deck.
But markets don’t reward experiments forever. As capital tightens and investors demand sustainable revenue models, startups built on hype, not fundamentals, will collapse.
History is clear: every tech wave has its Pets.com moment. AI will be no exception.
3. The Differentiation Dilemma
Right now, thousands of AI startups are building chatbots, productivity tools, and verticalized assistants. The problem? They all look and feel the same.
Without deep industry expertise, proprietary data, or defensible distribution, most of these startups are features, not companies.
The survivors will be those that carve out real moats—through unique data sets, domain knowledge, and integrations that can’t be easily copied by bigger players.
4. The Regulatory Reckoning
Governments worldwide are racing to regulate AI, from the EU’s AI Act to U.S. executive orders. While regulation is necessary, it will also raise compliance costs and add friction for smaller players.
Big Tech can afford armies of lawyers and compliance teams. Most startups cannot. This regulatory wave will disproportionately wipe out underfunded challengers.
5. The Talent Squeeze
AI talent is scarce—and expensive. The best researchers, engineers, and product leaders are being snapped up by the giants. Startups are left competing for scraps, often overpaying for teams that can’t match the depth of expertise sitting inside Meta, Google, or OpenAI.
Without elite talent, it’s nearly impossible to stay ahead in a field moving this fast.
What Comes After the Extinction
So, does this mean AI innovation is doomed? Far from it. In fact, the extinction event will be healthy.
It will clear the market of clones, hype-driven pitches, and unsustainable business models—making space for a new generation of companies that truly understand where AI creates value.
The winners will be:
- Startups with proprietary data and domain expertise.
- Companies that solve real, painful problems rather than chasing buzzwords.
- Builders who treat AI not as the product, but as an enabler—integrating it seamlessly into workflows, industries, and daily life.
The Bottom Line
The AI boom has been breathtaking, but it is also unsustainable in its current form. The next 24 months will bring a brutal contraction—thousands of startups shutting their doors, investors licking their wounds, and consolidation under Big Tech.
Yet in that crucible, the strongest ideas and founders will emerge. And just like the dot-com crash gave rise to Google, Amazon, and Facebook, AI’s extinction event will pave the way for the true giants of tomorrow.
The hype cycle is ending. The real work is about to begin.
Mehran Muslimi 