The AI Extinction Event Is Coming

Title: The AI extinction event is coming

Read time: 3 min

Today I want to discuss something that might ruffle a few feathers. That’s ok, I tell the truth, and clients pay us a lot of money to do so.

I believe most AI startups should not exist.

Right now we’re living through what feels like a gold rush. Every week there’s another AI product launching, another company announcing funding, another demo showing how a model can automate some task. It looks and feels like innovation is exploding.

When you look a little closer, something else becomes obvious.

A massive percentage of these companies are not building real businesses. They’re building wrappers around APIs, and models. Wrappers around capabilities that every other company can access too, and most of them are solving problems nobody urgently needs solved.

The result is an ecosystem full of technically impressive products that no one feels compelled to buy. That’s a dangerous place to build a company, because markets do not reward interesting technology, they reward urgency.

And when urgency is missing, companies slowly begin to disappear.

If the last decade taught us anything, it’s that hype cycles create far more startups than markets can support. AI will be no different. I believe the next 24 months are going to look like an extinction event for AI startups. It’s already happening.

A Rising Tide Lifts All Boats. It’s Not Until The Tide Goes Out Do You See Which Ones Are Swimming Naked.

~Warren Buffett

What’s Actually Happening In The AI Market

Right now it’s easier than ever to build a product. You can spin up infrastructure in minutes, access world-class models through an API, and ship something functional in weeks. This is incredible progress.

But it has created an unintended side effect, building is no longer the bottleneck. Validation is.

When everyone can build quickly, it somewhat levels the playing field. The market fills up with products that were never pressure-tested with real customers. Many founders start with the technology and then search for a problem.

They experiment with use cases, refine the UI, and continue adding features, but they rarely stop to ask the only question that matters.

Is this a problem someone urgently needs solved?

If the answer is no, the product may still be interesting. It just won’t become a business.

Why Most AI Products Feel the Same

Another dynamic showing up right now is sameness.

If you look across many AI categories, the differences between products are surprisingly small. One tool summarizes documents. Another summarizes documents slightly differently. One tool automates outreach. Another automates outreach with a slightly different workflow.

Underneath the hood, many of these companies are using the same models and the same infrastructure.

Which means the actual product advantage (moat) is thin.

When that happens, buyers stop evaluating technology and start evaluating something else entirely. They ask which vendor understands their workflow best, which one feels easier to implement, and which one actually understands their problem.

In saturated markets, the companies that win are rarely the ones with the most features. They’re the ones with the clearest understanding of the customer use cases, and how painful they are.

The Real Reason Startups Will Disappear

Startups don’t die because the technology stops working. They die because the problem wasn’t painful enough.

A product can be impressive and still fail. It can have great design, powerful automation, and even early users, but if the problem it solves isn’t urgent, adoption slows down quickly.

Buyers get distracted. Budgets shift. Projects get deprioritized. Eventually the product becomes something people thought about using, but never truly needed.

This is the graveyard of startups. Not in dramatic collapses, but slowly, through indifference. Prospects are just not interested.

The Mistake Many Founders Are Making

The most common mistake I see right now is starting with the technology.

A new model appears, a new capability becomes possible, and founders immediately begin building products around it. The most successful companies start in the opposite direction.

They begin with a painful problem. Something expensive. Something inefficient. Something organizations are already struggling with.

Only after the pain is clear do they build the solution.

This approach feels slower at first, but it produces companies that survive. Because if the problem is real, what I call a broken leg problem, buyers don’t need to be convinced.

They are already incapacitated, they’re searching for relief immediately. This is the T (timing) in BANT, or the I (identify pain) in MEDDPICC. The more pain, the more motivation. The more motivation, the higher the probability is they close.

What Founders Should Do Instead

If you want to avoid becoming another AI company that quietly disappears, start with the problem, not the technology. Talk to customers long before your product feels finished and spend time understanding where they are losing time, money, or operational leverage today. Look for the problems that already have budget attached to them, the ones teams are actively trying to fix right now. Sometimes this process takes years to really get it dialed in.

Then build the smallest possible solution that removes that pain and try to sell it early. If people are willing to pay for it before the product is perfect, you are probably solving something real. If they are not, you just saved yourself months of building the wrong thing.

When the problem is real, companies move fast. They find budget. They bring in the right stakeholders. They prioritize the solution.

And when the problem is not painful enough, something else happens, the product gets pushed to next quarter. Projects stall, or the buyer loses interest.

The AI Extinction Event

Over the next couple of years the market will sort itself out. Thousands of AI products will launch, but most of them will struggle to find real demand.

Some will pivot. Some will get acquired for talent. Many will quietly shut down.

A smaller group will survive.

Those companies will share a few things in common. They will solve problems that actually matter. They will understand their customers deeply, and they will build technology that removes real pain instead of simply showcasing capability.

The AI boom is creating an incredible wave of innovation, but waves eventually break.

When this one does, the companies that survive will not be the ones with the flashiest demos or the most features. They will be the ones solving problems people truly need fixed, and a well oiled machine to predictably close revenue and scale.

That’s it for today, folks.

See you all next week!

Darren


P.S. If finding PMF and scaling to $1M in ARR through founder-led sales is on your radar, book a call with me here

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