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Everyone keeps saying AI is crowded. What they’re not saying is that a third of it is already dead.
🎙️ In this episode, we get into:
- Where AI tools are being built and which cities are becoming serious hubs
- Why 4,000+ tools have already gone dark and what that churn reveals
- What the AI tool death toll teaches us about category collapse, market signals, and blind spots
- How to read the map so you’re not building in a dead zone or betting on noise
This isn’t a guess. It’s data we pulled ourselves. And it’s already changing how we think about where to build, invest, and win in AI.
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We’re the team behind whatisthat.ai, the AI discovery platform built to cut through all the hype, and WITAI Advisory, the strategic services arm helping founders and leadership teams turn AI exploration into execution.
If this all feels overwhelming, it’s not your fault. The landscape is moving too fast for most teams to keep up!💨
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Creators and Guests
What is AI on Air by whatisthat.ai?
An AI-generated podcast that rips the glossy marketing veneer off the AI industry and tells you what’s actually happening underneath — tools, takeovers, weird experiments, and the occasional digital chaos.
witai.substack.com
Broadcasting live from somewhere inside the algorithm, this is AI on air, the official podcast from whatisthat.ai, we're your AI generated hosts, let's get into it. Okay. Let's unpack this a bit. So there's this statistic floating around. Over 11,000 AI tools built, launched, supposedly out there changing the world.
Speaker 2:Sounds like a real gold rush, doesn't it?
Speaker 1:It really does. But here's the kicker, the sort of jolt. Mhmm. About a third of them already gone. Just offline poof.
Speaker 2:Vanished. Yeah.
Speaker 1:To me, that just screams, you know, intense experimentation and maybe, frankly, a bit of a shakeout happening right now.
Speaker 2:Oh, absolutely. What's really striking is just the sheer volume of attempts and how how quickly the whole landscape is shifting. It really shows how fast this field is moving. Right?
Speaker 1:Lots of ideas getting tested, like, in real time.
Speaker 2:Exactly. And that's that's precisely why we're doing this deep dive today. We're looking at a really fascinating report from what That dot AI, their AI tool report. And they're not just, you know, tracking mentions or hype. They're actually monitoring live AI tools and verifying the data, especially where these tools are coming from.
Speaker 1:Which is harder than it sounds, I bet. Definitely. They even mentioned they're working on a sort of future method using AI to analyze those terms of service agreements for location data.
Speaker 2:Oh, interesting. Because those dense legal documents, you know, they can sometimes tell you a surprising amount about a company's real priorities.
Speaker 1:Right. Like data handling or how they view different regulations.
Speaker 2:Exactly. Their comfort level maybe.
Speaker 1:So our mission here for this deep dive is pretty clear. We want to pull out the key insights. Where is AI development actually happening globally? And what is this like huge disappearance rate, this churn? What does it actually mean?
Speaker 2:Right.
Speaker 1:Whether you're building in this space or investing or maybe you're just, you know, fascinated by all this tech, this is really for you.
Speaker 2:Yeah. Because understanding these basic patterns, the geography of innovation, the, the mortality rate of these tools, it gives you a real edge, a way to make sense of a really complex, fast moving area.
Speaker 1:Okay. So let's jump in. First, big question. Yeah. Where are these tools actually being built?
Speaker 1:According to the report's verified data, The US, it's way out front, 1,182 tools, which I guess isn't totally unexpected.
Speaker 2:No. Not really surprising given the, you know, the established tech scene, the access to capital here. But but Yeah. It's really important to look beyond just that top number. The fact that other countries are showing significant activity too.
Speaker 2:That tells you it's a much broader global thing.
Speaker 1:Absolutely. Because right behind The US, you've got some serious players. The UK, for instance, they're next with a 25 tools. Then India, Eighty Three. Canada, Seventy Four.
Speaker 1:Germany's got 68. France, 40 three. Netherlands, 30 four. I mean, it's a pretty strong diverse group.
Speaker 2:It really is. And that international spread, it kind of suggests AI innovation isn't just stuck in one place. Different countries probably bring different strengths, different focuses, maybe different research priorities, you know.
Speaker 1:Okay. So let's zoom in a bit. From countries to cities. The report also pinpoints the top urban hotspots for AI development.
Speaker 2:In San Francisco.
Speaker 1:Still number one. Yeah.
Speaker 2:Awesome.
Speaker 1:370 tools, which, you know, fits the narrative. Major tech hub.
Speaker 2:It does fit the narrative. But here's what's really revealing, I think. Those 370 tools, that's only about what? 18% of the total verified tool?
Speaker 1:Exactly. Which means, doing the math, over 80% of these AI tools are starting up somewhere else. Right. That really challenges that whole idea that AI innovation is only a Silicon Valley story.
Speaker 2:It really does. And that distribution, that's a key takeaway here. SF is influential, sure, but the data clearly shows a much more dispersed landscape.
Speaker 1:Yeah.
Speaker 2:You've got cities like New York, Hundred And Twenty Nine tools. London, a hundred and three. Those are major centers in their own right.
Speaker 1:And it doesn't stop there. You see Mountain View, Paris, Singapore, Berlin, Palo Alto, LA, San Jose, all in the top 10. Plus, the report specifically flags London, Toronto, Bangalore, Berlin, and Tel Aviv as serious emerging hubs.
Speaker 2:And they mentioned reasons, right, like access to engineer?
Speaker 1:Yeah, speed, cost maybe.
Speaker 2:Right. Those concentrations in specific cities, probably reflects existing tech infrastructure, strong universities, pumping out talent, good investor networks, mentors.
Speaker 1:And
Speaker 2:the growth in these other hubs suggests those enabling factors are spreading out globally.
Speaker 1:But it's not just the big guys, is it? The report also highlights some, small players on the rise, which I thought was really interesting. Estonia, Switzerland, and Israel.
Speaker 2:Yeah. What's kind of remarkable there is that their output, the number of AI tools, seems pretty high compared to their population size or even their overall tech sector size.
Speaker 1:Right. Disproportionately high. They called Estonia the Davos of digital. Yeah. Suggests a very, like, forward thinking digital environment.
Speaker 2:Mhmm. And Switzerland, described as neat, clean, quietly AI forward.
Speaker 1:Which paints a picture, doesn't it? Yeah. Maybe a more measured approach, but still really effective.
Speaker 2:Quietly effective. Yeah. And Israel well, Israel's always been strong in tech innovation. The report notes their strength in areas really crucial for AI, like cybersecurity, core infrastructure.
Speaker 1:That foundational stuff.
Speaker 2:Exactly. That expertise probably helps support building all sorts of AI applications on top.
Speaker 1:Okay. So this all leads to a really basic question. Why should we even care where these tools are being built? It's more than just dots on a map.
Speaker 2:Precisely. Location gives you critical context. It hints at the regulatory world a tool lives in.
Speaker 1:Right.
Speaker 2:The availability of certain skills, investment climate, maybe even like the basic assumptions baked into the tool about data privacy.
Speaker 1:Right.
Speaker 2:Essentially, it gives you a deeper read on the environment that's shaping that AI.
Speaker 1:It's all part of what they call AI market intelligence.
Speaker 2:Exactly that. Understanding these geographic clusters, it gives you a real strategic advantage potentially. Yeah. It just allows for more informed decisions whether you're thinking about investing some more specific or just trying to figure out the competition in a market.
Speaker 1:Okay. Let's shift gears then to the other really big finding in this report. The churn rate.
Speaker 2:Yes. The churn.
Speaker 1:Out of those, was it 11,266 tools they tracked, nearly 4,000 are already gone, ceased to exist.
Speaker 2:That is a lot of attrition.
Speaker 1:It really is.
Speaker 2:And it just underscores how incredibly dynamic this AI space is right now. And, pretty competitive too. Yeah. We're seeing just rapid fire experimentation. And, you know, naturally, not every single attempt is gonna stick.
Speaker 2:Not every idea is viable long term.
Speaker 1:The report paints a pretty vivid picture. Disappearing founders, websites that just die, entire categories that seem to pop up and then just collapse.
Speaker 2:It sounds very, Darwinian, doesn't it?
Speaker 1:It really does. A Darwinian environment for AI tools.
Speaker 2:Well, that kind of high volatility, it's pretty typical for a rapidly emerging market. There's tons of exploration, testing different angles
Speaker 1:Right.
Speaker 2:And a big chunk just won't find a sustainable path. It'll be really interesting when they dig into why these tools failed. That analysis could be super valuable.
Speaker 1:Definitely something to watch for. But okay, for you listening right now, why does all this matter? The location stuff, the high failure rate. What's a practical takeaway?
Speaker 2:Well, about it. If you're trying to hire AI talent, knowing where the big development hubs are gives you a huge leg up in your search.
Speaker 1:Good point.
Speaker 2:Similarly, if you're scouting for promising startups, or maybe potential acquisitions, understanding these clusters helps you focus where innovation is most likely bubbling up.
Speaker 1:And if you're thinking about expanding your own AI work, knowing where the next wave might be coming from, that informs your strategy, right? Yeah. Market entry, potential partners.
Speaker 2:It's really more than just geography. It's about getting a grip on the underlying market dynamics. The flow of talent, where the money's concentrating, the regional strengths that help create these tools in the first place.
Speaker 1:The report also mentioned briefly some other interesting data points they're tracking, not just location.
Speaker 2:Right. Like churn rates within specific AI categories.
Speaker 1:Yeah. And the link between, like, search demand, what people are looking for, and the actual number of tools available.
Speaker 2:Mhmm. And identifying categories that are shrinking versus ones that still seem wide open.
Speaker 1:That seems useful.
Speaker 2:Yeah. Looking at trends, like how often people search for AI video generator versus how many actual tools exist. That can tell you a lot about whether a niche is getting saturated or if there are still gaps, unmet needs.
Speaker 1:And they made a really smart point. High churn isn't always bad news for you.
Speaker 2:How so?
Speaker 1:Well, seeing a lot of tools fail in one specific category, that could be a pretty strong signal that maybe that's not the area to pour your own time and money into.
Speaker 2:Right. A signal of what not to do, learning from others' failures.
Speaker 1:Exactly.
Speaker 2:That can be just as valuable as spotting the successes. Helps you avoid crowded or maybe just unsustainable market segments.
Speaker 1:So, okay, boiling it all down, what's the key takeaway here? The core message from this deep dive into the AI tool report that you should really hang on to?
Speaker 2:I think the fundamental message is understanding both where AI is being built and the, the significant rate tools are dying off, that gives you a crucial strategic advantage.
Speaker 1:Mhmm.
Speaker 2:It's about looking past the surface hype, know. Really getting the lay of the land in this super fast changing field. It helps you spot the opportunities and maybe navigate the pitfalls.
Speaker 1:So quick recap then. US leads in sheer numbers, but definitely not alone. Yeah. UK, India, Canada, others are major players too.
Speaker 2:Right. It's diversifying.
Speaker 1:We're seeing key city hubs pop up globally. Yeah. Way beyond Silicon Valley. Think London, Toronto, Bangalore. Bangalore.
Speaker 2:And smaller nations like Estonia, Switzerland, Israel are really punching above their weight.
Speaker 1:And maybe the biggest point, that super high churn rate, it just highlights how dynamic and yeah, how competitive this AI space is right now.
Speaker 2:Which kind of leads us to a final thought for you to mull over.
Speaker 1:Okay.
Speaker 2:Given this huge failure rate, what fundamental shifts do you think the surviving tools will actually represent? What core value, what tech edge will define the ones that actually make it and thrive?
Speaker 1:That's a good one. Or maybe thinking about those geographic clusters we talked about. Knowing where innovation is bunching up now, what new kinds of collaboration or maybe even new competitive rivalries might we see emerge as these hubs grow and maybe start connecting more in the few years.
Speaker 2:Definitely some interesting things to chew on there. That's it for this episode of AI on Air powered by WhatIsThat.ai. If your brain survived this episode, go ahead and subscribe. We drop new episodes every week. Wanna go deeper?
Speaker 2:Join our community on Substack to get early drops, tool breakdowns, and weird AI stuff the mainstream hasn't caught yet. See you there.