The Rise and Fall of the Most Overhyped AI Startups part 2

AI startups are raising billions. But here’s the dark secret: most of them are dying. According to the MIT report, 95% of generative AI pilots at companies are failing, so what happens to AI startups that are building pilots? Big visions. Bold promises. And yet, one by one… crash and burn. Today, we’re exposing the biggest AI startup failures and why having great tech is never enough. Here’s the Rise and Fall of the Most Overhyped AI Startups, part 2. By the way, if you’re interested in part 1, here it is.

Ansaro: AI for Hiring, but nobody was hiring it

On paper, Ansaro had everything. A $3 million seed round. A small but talented six-person team. And a clear mission: reinvent the hiring process.

Ansaro pitched itself as “Improve all hiring and workforce decisions with data-driven insights.” Its system promised to combine predictive analytics with structured interviews. They even built a sleek AI notetaker for recruiters. The goal was bold: eliminate bias, improve the quality of hire, and change the way companies bring people on board.

But here’s where the cracks showed.

Ansaro couldn’t build a customer base with meaningful customer data. Companies were hesitant either for privacy reasons or because they simply didn’t trust the concept of AI recruiting. Co-founder Sam Stone later admitted: “The disadvantage was that these models were not ready to be put into production.” In other words, the tech looked good in theory, but it wasn’t robust enough for messy real-world data.

Then there was the user mismatch. Ansaro sold to CHROs and HR leaders, but the people actually using the tool were recruiters. Recruiters weren’t obsessed with “quality of hire.” Their pain point is about the speed. What they care about is ‘How fast can I fill this role?’ Ansaro was solving for the wrong pain point.

Sales also didn’t scale. Much of their traction came from the founder’s personal charisma and network. That’s not a repeatable sales strategy.

And then there was competition. By the time Ansaro launched, applicant tracking systems like Lever, Snaphunt, and Greenhouse already had strong footholds. Their pitch—“we help you find candidates faster” was more practical than Ansaro’s pitch of “we’ll predict long-term hiring success.”

The only feature that stood out? The notetaker. But let’s be real: that wasn’t enough to justify a new platform. Recruiters shrugged, and Ansaro fizzled.

Ansaro’s story is a textbook example of a great idea, but they’re resolving the wrong problem with wrong execution.

Olive AI: From Unicorn to shutdown

Olive AI wasn’t just a startup, it was a juggernaut. At its peak, it raised close to $1 billion in funding and was valued at $4 billion. Its promise? To be the AI operating system for healthcare.

The pitch was intoxicating. Healthcare is bloated, inefficient, and paperwork-heavy. Olive claimed it could automate everything from insurance claims to hospital admin. Investors lined up. Headlines called Olive “the future of healthcare AI.”

But here’s the uncomfortable truth: Olive never had focus.

Instead of nailing one problem, the company kept pivoting. Claims processing. Then supply chain. Then patient records. The roadmap changed so often that employees joked they needed GPS just to keep up.

The leadership culture didn’t help. Reports described a toxic workplace—long hours, poor communication, and even unethical practices. One former employee said: “The product wasn’t the problem. Leadership was.”

And then came the spending. Olive burned through its massive war chest like there was no tomorrow. Insiders described a “champagne and cocaine” mentality—lavish spending, poor discipline, zero accountability.

The result? Layoffs. Investor skepticism. And eventually, collapse. By 2023, Olive shut down and sold its assets for scraps.

“One, learn a lot about things that matter. Two, work on problems that interest you and three, with people you like and respect. If you’re interested in genuinely interesting problems, gratifying your interest energetically is the best way to prepare for a startup. – Paul Graham”

My takes & Looking forward

So what’s the big takeaway? Having a cool AI tool isn’t enough. Tech doesn’t sell itself. Success comes when startups align innovation with customer needs, trust, and adaptability.

Because let’s face it: 90% of startups fail. However, if you solve a real problem, focus on the customer, and adapt quickly, you might just be in the top 10%.

Now, I want to hear from you what do you think is the number one reason AI startups fail? Drop your thoughts in the comments. 

If you found this article helpful, follow me here or sign up for my weekly free newsletter and consider upgrading to premium on my Substack for early access to high-quality tech content. I’m an entrepreneur who covers the real stories behind AI startups, funding, and innovation, minus the fluff and noise, and I practise my entrepreneurial muscles every week. Check out part 1 of the AI startup series or this blog about Perplexity’s offer to Google Chrome. Comment down below, I would love to hear your thoughts. I read and reply to everyone, and thank you again for being here.