Original research · Updated August 24, 2026

Which AI tool categories fail most

Not every corner of the AI market dies at the same rate. We rank every category in our catalogue by the share of its tools that have since shut down or been acquired and sunset — measured against the tools we actually tracked, not estimated from the outside.

Failure rate range · 37 categories2.2%–16.1%a 7× spread

Where a tool sits matters more than the market-wide average. The safest category we track is Engineering & Simulation at 2.2%; the riskiest is Automotive at 16.1% — 7 times likelier to be dead. Across the whole catalogue the rate is 9.9%.

Among major categories (50+ tracked tools), BI & Analytics leads at 9.4% — 12 of 127 gone. Smaller categories can post higher rates off a handful of deaths, so read the sample column alongside the rate.

Failure rate by category

37 categories · min sample 12
#CategoryFailure rate
1Automotive16.1%5 / 31
2E-Commerce12.5%6 / 48
3NSFW12.1%4 / 33
4Coding Assistants9.8%4 / 41
5Browser Agents9.5%2 / 21
6BI & AnalyticsMajor9.4%12 / 127
7Developer ToolsMajor8.8%28 / 320
8AI Content WritingMajor8.7%15 / 172
9Customer SupportMajor8.6%12 / 139
10AI Art & Image CreationMajor8.2%15 / 183
11Voice AIMajor8.1%5 / 62
12Gaming & 3D Modeling8.0%2 / 25
13AI/ML ModelsMajor7.1%12 / 169
14Science & ResearchMajor7.1%4 / 56
15Fitness & Lifestyle7.1%2 / 28
16HealthcareMajor6.7%7 / 104
17ProductivityMajor6.0%14 / 234
18AI InfrastructureMajor5.8%18 / 311
19AI Audio CreationMajor5.8%5 / 86
20Workflow AutomationMajor5.3%12 / 225
21Education & LearningMajor5.3%5 / 94
22Social Media ManagementMajor5.2%3 / 58
23Finance & TradingMajor5.1%5 / 99
24AI AgentsMajor5.0%16 / 319
25Music Creation4.8%1 / 21
26Marketing & SEOMajor4.5%8 / 176
27Legal Assistant4.2%2 / 48
28Real Estate4.2%1 / 24
29Video CreationMajor4.0%5 / 126
30No-Code / Low-CodeMajor3.8%3 / 79
31Sales & RevOpsMajor3.6%7 / 193
32AI SDRs3.3%1 / 30
33LLM Observability & Evals3.3%1 / 30
34Vector DBs & RAG2.9%1 / 35
35Security & GovernanceMajor2.7%4 / 148
36LLM Gateways & Serving2.7%1 / 37
37Engineering & Simulation2.2%1 / 46

Categories with fewer than 12 tracked tools are excluded: one death in a category of three is a 33% rate that means nothing. Rates are calculated against every tool we have ever catalogued in that category, including the ones still running.

How this is measured

Numerator

Tools in that category that shut down, or were acquired and had the brand retired. Acquired tools still shipping under their own name are not counted as dead.

Denominator

Every tool we have ever listed in that category, at any lifecycle. Both halves come from the same catalogue, so the rate holds regardless of how complete our coverage is.

Provenance

Every retirement is hand-reviewed, sourced and dated by an editor — never auto-scraped. The raw dataset is public at /feed/graveyard.json.

Cite this

ToolDirectory.AI, "Which AI Tool Categories Fail Most" (as of August 24, 2026): AI tool failure rates range from 2.2% (Engineering & Simulation) to 16.1% (Automotive) across 37 categories — a 7× spread. Among categories of 50+ tracked tools, BI & Analytics is highest at 9.4%. https://tooldirectory.ai/research/ai-category-failure-rates

Free to quote with attribution under CC BY 4.0. Figures move as the dataset grows — please cite the date alongside the number.

Questions

Which AI tool category fails the most?

Automotive, at a measured 16.1% failure rate — 5 of the 31 Automotive tools ToolDirectory.AI has catalogued are gone, as of August 24, 2026. Among larger categories (50+ tracked tools), BI & Analytics is highest at 9.4%. Every ranked category clears a floor of 12 tracked tools, but read the sample size alongside the rate: smaller categories move further on a single shutdown.

How much do AI failure rates vary by category?

Substantially — from 2.2% (Engineering & Simulation) to 16.1% (Automotive) across the 37 categories we rank, a 7× spread. The whole-catalogue rate is 9.9%, so a market-wide average understates the risk in the worst categories and overstates it in the safest.

What are the riskiest AI tool categories?

BI & Analytics (9.4%), Developer Tools (8.8%), AI Content Writing (8.7%), Customer Support (8.6%), AI Art & Image Creation (8.2%) — ranked by the share of catalogued tools that are now gone, across categories with at least 50 tracked tools. The full table on this page ranks every category down to a floor of 12.

How is the category failure rate calculated?

Dead tools in a category divided by every tool we have ever catalogued in that category, at any lifecycle. A tool counts as dead if it shut down, or was acquired and had its brand retired; acquired tools still shipping under their own name are excluded from the numerator. Categories with fewer than 12 tracked tools are excluded entirely, because rates on tiny samples are noise.

Is this the same as the AI startup failure rate?

No. Commonly cited AI startup failure figures (80–90%) are company-level estimates. This is measured at the product level inside a fixed catalogue: of 2,728 AI tools tracked, 271 (9.9%) are gone. The per-category rates on this page break that number down by what the tool actually does.

Why do some AI categories fail more than others?

The pattern in our data is concentration risk: categories sitting closest to a foundation-model vendor's own roadmap lose tools fastest, either absorbed by acquisition or undercut by a native feature. Categories built on workflow and integration depth retain tools longer. We publish the rates rather than the theory — the underlying dataset is public at /feed/graveyard.json.

How current is this data?

It is computed live from the Graveyard on every rebuild, so it is current as of August 24, 2026. Every entry is hand-reviewed, sourced and dated by an editor rather than auto-scraped.

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