TL;DR: The AI boom is exciting, but a shocking number of AI ventures are failing fast. The "AI Graveyard" on Dang.ai shows nearly 1,700 AI tools have shut down by May 2024, about a quarter of those tracked. Many are "thin wrappers" around existing tech like GPT, lacking real value or a solid business model. For entrepreneurs, investors, and even users, this digital cemetery offers crucial lessons: focus on differentiation, core value, and sustainable business models, or risk becoming another digital tombstone.
The air is electric with AI, isn't it? It feels like we're on the cusp of a new industrial revolution, with AI tools sprouting up like mushrooms after a spring rain. Every day, we hear about groundbreaking innovations and how artificial intelligence is set to transform every facet of our lives and businesses. And much of this excitement is justified. At Mercury, we're deeply invested in harnessing the power of AI to [create real value for our clients]
However, amidst this gold rush, it's crucial to take a step back and look at the landscape with a clear head. Let's pour a little cold water on the fever pitch and examine a sobering reality: the AI boom is also creating a rapidly growing graveyard of failed ventures.
A Stroll Through the "AI Graveyard"
I recently came across a fascinating, if somewhat grim, the [AI Graveyard] Hosted on the tool aggregator site Dang.ai, this section serves as a digital cemetery for AI products that have "died young" – those that have ceased operations, been acquired and shuttered, or simply vanished
As of my last check, the AI Graveyard lists 1,698 defunct AI tools. Dang.ai tracks around 5,670 tools in total, meaning nearly 30% of the AI tools launched have already bitten the dust. In 2024 alone, 624 new "bodies" have been added to this list.
Just in the last 7 days, 19 tools were laid to rest. Think about that. Nearly one in three AI tools featured on a major aggregator has failed. This isn't to spread doom and gloom, but to inject a healthy dose of realism into the AI conversation. This "graveyard" is a powerful window into the inherent risks and potential frothiness of any major tech wave.
The Usual Suspects: Why AI Ventures Are Failing
The "Thin Wrapper" Syndrome
This is a big one, folks. Many of the tools we see are, to put it bluntly, light repackagings of existing, powerful APIs – think OpenAI's GPT models, for example. They might offer a slightly different user interface or focus on a very specific niche, but they add very little in terms of core technological innovation or proprietary data. The challenge here is stark: when the underlying engine is accessible to everyone, and the cost of using those foundational APIs continues to fall, these "thin wrappers" find it incredibly difficult to justify their existence and, crucially, their price point. Value, in this game, needs to be more than skin deep.
Product Homogenization
Directly linked to the "thin wrapper" issue is the problem of product homogenization. If your AI tool essentially does the same thing as a dozen others, with no significant, tangible differentiator, you're entering a brutal race to the bottom. The market becomes saturated with look-alikes, and users have little compelling reason to choose your offering over another, or more importantly, to stick with it. We're seeing this play out vividly in the realm of writing and text generation tools – currently the most common category in the AI Graveyard – closely followed by image generation and various chat-related tools. If you can't answer "Why you?" clearly and convincingly, the market will answer for you.
Low Barrier to Entry (for the basics)
Let's be clear: creating truly foundational AI models is an incredibly complex, capital-intensive, and time-consuming endeavor. However, slapping a new interface on an existing API and calling it a new product? The barrier to entry for that is distressingly low. This ease of creation for "thin wrapper" products means the market gets flooded with similar offerings, making it extraordinarily difficult for any single one to gain meaningful traction and escape the noise.
Funding Woes & Unsustainable Business Models
The "build it and they will come" philosophy, fueled by venture capital, often translates to "burn cash rapidly and hope to capture market share before figuring out a viable, long-term business model." This is a high-wire act without a safety net. If user acquisition costs are sky-high, if customer churn is rampant because the product isn't sticky enough, or if the AI tool doesn't solve a painful enough problem that people will consistently pay for, the funding inevitably dries up. Hype can attract initial investment, but it can't sustain a business indefinitely.
Lack of a Moat
What's your defensible advantage? Your "moat"? If your answer is a slick UI or a clever marketing slogan, I'm afraid that's not enough – not by a long shot. True, defensible moats in the AI space come from things like unique and proprietary datasets, genuinely novel algorithms, deep domain expertise that's intrinsically woven into the AI's functionality, or a strong, engaged, and loyal community. Without these, competitors can, and will, easily replicate your offering. When a product's perceived value lies only in its superficial layers, rather than in a robust core model or a significant data advantage, it’s incredibly vulnerable once the initial novelty and hype subside.
Lessons from the Digital Tombstones
The AI Graveyard isn't just a macabre collection of failed ventures; it's a rich and accessible source of learning.
For Investors: It’s a rapid screening database for business model durability. See what’s failed and why before committing capital. The patterns are often there to see.
For Product Managers & Entrepreneurs: Consider it a "mirror of failure." Before you even sketch out your Minimum Viable Product (MVP), take a walk through the graveyard. See what has already been tried, what became of similar predecessors, and learn from their mistakes. This can save you a world of pain and wasted resources.
For Curious Users & Tech Enthusiasts: It’s a living lesson in the real淘汰率 (elimination rate, for our non-Mandarin speaking friends – it means the dropout or washout rate) of this AI wave. It helps all of us understand the crucial difference between transient hype and lasting, impactful innovation.
Building an AI Future That Lasts: Beyond the Hype
So, if you're an entrepreneur dreaming of launching the next groundbreaking AI innovation, or perhaps a business leader looking to strategically adopt AI into your operations, should you be discouraged by this? Absolutely not. But you should be ruthlessly strategic.
The promise of AI is immense; I truly believe that. But building a successful, sustainable AI venture or integrating AI effectively into an existing business requires far more than just raw enthusiasm for the technology. It demands a clear-eyed approach focused on:
True Differentiation:
Don't just be another wrapper. Ask the hard questions: What unique problem are you solving? What unique technology, data, or approach do you bring to the table that others don't? At Mercury Technology Solution, for instance, we focus on integrating AI to solve specific, tangible business challenges. This is evident in our Mercury ContentFlow AI Suite, which is designed to revolutionize e-commerce content creation by deeply integrating AI into the workflow, or our Muses AI assistant, which provides practical operational support for businesses. It’s about solving real-world needs in a novel way.
A Solid Business Model:
This seems obvious, but it’s shocking how often it’s an afterthought. How will you create ongoing value that customers are willing to pay for, consistently? You need to deeply understand your customer, their most pressing pain points, and precisely how your AI solution provides a compelling and, critically, sustainable Return on Investment (ROI).
A Deep Moat:
As I mentioned, you need to build defensibility. This can come from proprietary technology, unique and hard-to-replicate data sets, strong network effects (where the product becomes more valuable as more people use it), or deep integration into customer workflows that makes your solution indispensable. Our customized AI integration solutions, for example, are specifically designed to work with clients to build these deep moats, tailoring AI to their unique operational landscapes.
Focus on Core Value:
Don’t get distracted by the shiniest new object or the latest buzzword. Ensure your AI application delivers tangible, measurable benefits and solves a real-world problem more effectively or efficiently than existing alternatives.
The AI revolution is undeniably real, but like all significant technological shifts, it will have its casualties. The AI Graveyard serves as a stark reminder that innovation, when untethered from a sound strategy and genuine differentiation, often becomes a fast track to obsolescence.
If you're contemplating a dive into AI entrepreneurship, or if you're simply curious about which ideas have already been tested and found wanting, I genuinely encourage you to take a metaphorical walk through this digital cemetery. Among the tombstones, you might just find the critical insights you need to build an AI venture that not only survives the current shakeout but thrives for years to come.
What are your thoughts on the AI boom and its long-term sustainability? Where do you see the biggest pitfalls and the greatest opportunities? I’d love to hear your perspective.
