The AI graveyard report: what kills AI tools, by the numbers (2026)

We run an AI graveyard — a standing record of the AI tools that have shut down, gone dark, or been acquired. As of June 2026 it holds 170 entries, and that number is the point of this report. Most coverage of dead AI tools is anecdotal: one famous flameout, one splashy shutdown post. We have something more useful — a structured dataset of how AI tools actually die. So we ran the numbers on all 170. This is what kills an AI tool in 2026, by cause, by year, by category, and by who is doing the acquiring.

We catalog these products for a living, which means we are also the ones who watch them end. We are not neutral observers; we maintain the dataset by hand, and we will be specific about what it shows and where its edges are. For the names behind the numbers, the AI graveyard is the running record this report is built on.

Key findings

• 170 AI tools in our graveyard as of June 2026: 105 died outright (62%) and 65 were acquired (38%). For an AI tool, getting bought is nearly as common an ending as dying.
• The most common cause of death is a quietly expired domain — 40% of all entries. Among the tools that died rather than sold, 64% simply let their domain lapse with no shutdown announcement at all.
• The death rate is accelerating. Recorded deaths and acquisitions went from 22 in 2023 to 44 in 2024 to 73 in 2025 — roughly tripling in two years.
• NVIDIA is the single most active acquirer in the dataset, absorbing six of the tools we tracked — more than twice any other buyer.
• The deadliest categories by raw count are Developer Tools (24), AI art and image creation (18), and AI infrastructure (17) — the most crowded, most-hyped corners of the market.

How we built this report

The dataset is the 170 tools in our graveyard — every entry whose lifecycle we have marked deceased or acquired. Each one carries, where we could establish it, a cause of death, a date, one or more categories, and (for acquisitions) the acquirer. The snapshot for this report was taken in June 2026.

Five caveats, because the method shapes the numbers and we would rather show our work than launder it:

1. This is our catalog's graveyard, not a census of every AI startup. It covers the tools we tracked closely enough to follow to the end — skewed toward products notable enough to have been listed in the first place. It is a large, hand-maintained sample, not the whole population.
2. "Domain expired" describes how a quiet death surfaces, not always the underlying business reason. When a tool stops announcing anything and its site goes dark, the first hard evidence we get is a dead domain. That is itself a finding — most tools die without a word — but read it as "went dark," not as a root-cause diagnosis.
3. Category figures are absolute death counts, not death rates. We do not publish them as a percentage of all tools in each category, because crowded categories naturally produce more deaths. "Most deaths" is not the same as "most dangerous."
4. 2026 is a partial year, and quiet deaths surface late. We often confirm a death months after the fact, so recent-year counts are floors that will rise, not final tallies.
5. Acquisition is an ending, not a verdict. We count an acquired tool as leaving the independent market; some live on inside the acquirer, many are quietly wound down. More on that below.

Bought or buried: 38% of endings are acquisitions

The first thing the data settles is a framing we have used before: in 2026 the AI market sorts its exits into bought and buried, and the split is closer than you might guess. Of 170 endings, 65 (38%) were acquisitions and 105 (62%) were outright deaths.

That is a strikingly high acquisition share for any software category. It says the AI shakeout is not only a graveyard — it is also a clearance sale. A meaningful slice of the tools that stop existing as independent products do so because someone bought the team, the technology, or the customer list, not because the lights went out. We walked through the strategic logic of that in our piece on the 2026 AI consolidation; the dataset puts a number on it.

The catch, for anyone reading an acquisition as a happy ending: a sale and a shutdown often look identical from the user's side. The product gets absorbed, the standalone tool is sunset, and the thing you were paying for is gone either way. "Acquired" is a better outcome for founders and investors than for the people who depended on the product.

Most AI tools die quietly

Here is the finding we did not expect to be so lopsided. The single most common cause of death in the graveyard is not a shutdown announcement, a pivot, or a failed fundraise. It is a domain that simply stopped resolving — 68 of 170 entries, 40% of the whole graveyard.

Narrow it to the tools that died rather than sold, and the pattern is starker: 64% of outright deaths were silent. No farewell blog post, no "thank you to our users," no wind-down email. The company stopped paying for its own website, and that was the obituary. Announced shutdowns — the kind that make the rounds on tech Twitter — account for only about a third of real deaths (34 entries).

The lesson for anyone evaluating an AI tool is uncomfortable: the market's failure mode is not drama, it is disappearance. The tool you are trialing today is far more likely to vanish without notice than to send you a graceful shutdown notice. That is exactly why vendor durability has become a real input to AI buying decisions, a theme we keep returning to in our AI capex analysis.

The death rate is accelerating

The graveyard is filling faster every year. Entries by year of death or acquisition:

The count doubled from 2023 to 2024 and rose another two-thirds in 2025, for a roughly threefold increase across two years. 2026 already holds 23 entries, and because quiet deaths surface on a lag, that figure will climb well past where it sits today.

This is the downstream shadow of the funding boom. The 2023–2024 vintage of AI startups — the wave launched in the year after ChatGPT — is now hitting the point where seed runway runs out and Series A either lands or doesn't. A rising death count is what the back half of a hype cycle looks like in the data, and it lines up with what we are seeing on the human side of the same shift in where AI is actually replacing jobs.

Who is buying the survivors

Acquisitions cluster, and they cluster around infrastructure. The most active acquirer in our dataset is NVIDIA, which absorbed six of the tools we tracked — more than double any other buyer. Behind it sits a tier of repeat acquirers at two apiece, including Meta, Google, Databricks, Thomson Reuters, and Uniphore.

NVIDIA topping the list is not a coincidence; it is the consolidation thesis showing up in primary data. The company that sells the picks and shovels is also buying the businesses that make its hardware run better — inference optimizers, model-tuning shops, the layer between the model and the chip. The rest of the active buyers are either infrastructure platforms assembling a stack (Databricks, Google) or incumbents bolting AI onto an existing suite (Thomson Reuters in legal, Uniphore in customer experience). Almost none of the acquirers are themselves AI-native startups. The money flowing into these deals is coming from the layers of the market that already had revenue.

The deadliest categories

Where do AI tools go to die? By raw count, the graveyard is concentrated in the categories that were easiest to start a company in and hardest to defend:

Read this with the caveat from our method note: these are absolute counts, not rates, and the busiest categories will always post the most deaths. But the shape is still informative. Developer tools, image generation, and content writing — the categories where a small team could ship a wrapper on a frontier model in a weekend — are exactly where the casualties pile up. Low barriers to entry cut both ways: easy to launch, brutally hard to keep a moat once the base models absorb your feature. The AI infrastructure presence on this list is a different story — that is where the acquisitions concentrate, so a high count there reflects buyouts as much as burials.

What this means for AI tool buyers in 2026

The graveyard is, in the end, a buyer's tool. Three things it should change about how you evaluate AI products:

Assume disappearance is the base rate, not the exception. With 40% of deaths arriving as a silently dropped domain, "will I get a heads-up before this tool goes away" is the wrong question. Build an exit plan — data export, a fallback option — into any AI tool you come to depend on, especially the small ones.

Treat acquisition as an ending, too. A 38% acquisition share means a product you adopt has a real chance of being bought and folded into something else within a couple of years. That is not necessarily bad, but it is a change you should price in for anything mission-critical.

Weight the category. A new entrant in developer tools, image generation, or content writing is launching into the most heavily populated wing of the graveyard. The product can still be excellent — but the category's track record says durability is the thing to scrutinize hardest. Our editorial review methodology leans on exactly these signals, and the Top 100 AI Tools is our running answer to which products have cleared the bar.

Frequently asked questions

How many AI tools have shut down or been acquired? In our AI graveyard, 170 as of June 2026 — 105 that died outright and 65 that were acquired. That is the count of tools we have tracked to a confirmed end; it is a large hand-maintained sample, not a census of every AI startup, and it grows every month.

What is the most common reason AI tools fail? A quiet disappearance. The single most common cause of death in our data is an expired or dead domain — 40% of all graveyard entries, and 64% of the tools that died rather than being acquired. Most AI tools do not announce a shutdown; they simply go dark when the company stops paying for its own website.

Are more AI tools dying in 2026 than before? Yes. Recorded deaths and acquisitions rose from 22 in 2023 to 44 in 2024 to 73 in 2025 — roughly tripling in two years — as the post-ChatGPT startup wave runs out of runway. 2026 already holds 23 confirmed entries, and that number will rise as late-confirmed deaths surface.

Who is acquiring failed or struggling AI startups? Infrastructure players, led by NVIDIA, which is the most active acquirer in our dataset with six buys. Other repeat acquirers include Meta, Google, Databricks, Thomson Reuters, and Uniphore. Most buyers are infrastructure giants or incumbents adding AI to an existing product — rarely other AI-native startups.

Which AI categories have the most failures? By raw count, developer tools (24), AI art and image creation (18), and AI infrastructure (17) lead the graveyard. These are the most crowded, lowest-barrier categories — easy to launch in, hard to defend once frontier models absorb the feature. Note these are absolute counts, not death rates.

Is getting acquired good or bad for users? Mixed, and often it looks the same as a shutdown from the user's seat. A sale is usually a good outcome for founders and investors, but acquired products are frequently sunset or absorbed into the buyer's platform, so the standalone tool you relied on can disappear either way. Treat an acquisition as a possible ending, not a guarantee of continuity.

How do you track which AI tools are dead? We maintain lifecycle status (active, deceased, or acquired) on every tool in our catalog, with a cause of death, a date, and — for acquisitions — the acquirer. Quiet deaths are confirmed by monitoring for dead domains and missing sites; announced shutdowns and acquisitions are logged from primary reporting. The full roster lives in the AI graveyard.

Where to go next

For the names and stories behind these numbers, the AI graveyard is the running record, and our earlier roundup of the AI tools that died or got acquired walks through the notable cases. For the forces driving the trend, our AI consolidation analysis covers who is buying and why, and the AI capex bubble covers the spending that funds — and eventually starves — these companies.

The honest version: a graveyard with 170 entries and a tripling death rate is not a sign that AI is failing. It is a sign that AI is maturing — that the easy-to-build, hard-to-defend middle is being cleared out, while value consolidates into infrastructure and the products with real moats. The job of a buyer in 2026 is to tell which side of that line a tool is on before you depend on it.

— The ToolDirectory.AI editorial team