AI Content Errors: The 14 Mistakes That Reach Published Pages
We audited 80 of our own AI-assisted posts and catalogued every error that had made it to a published page. Fourteen distinct types, and almost none of them were bad writing. The prose was fine. What failed was everything a reader would have to leave the page to check: prices, product names, capabilities, links, statistics and counts. This is the list, ordered by how often each occurred, with the check that catches it.
The point of ordering it this way is that most editing effort goes into the wrong half. Nobody publishes an incoherent paragraph. People publish confident, well-formatted, wrong facts constantly.
Key Takeaways
- Roughly half of all checkable prices were wrong, and nearly every error made a product look cheaper or more generous than it is (audit of 80 posts, 2026-09-02/03, ANALYSIS).
- Five recommended products did not exist — two invented product names, one parked domain, one domain for sale, and a fitness wearable reviewed as a to-do app.
- Two posts described controlled tests that were never run, with timings quoted to the second and no dataset.
- The errors cluster in what a reader must leave the page to verify. Prose quality is not the signal.
- Every one of the 14 is caught by opening something — a pricing page, a product page, a link, a source.
How this list was made
530 published posts were pulled to local files. 80 were reviewed claim by claim, selected by search impressions. Every product was checked against the vendor's own domain, every price against the vendor's own pricing page, every link resolved through its redirects, and every statistic traced to a named source.
The frequency ordering below reflects that sample. It is our corpus, not a survey of the industry, and nothing about how those posts were produced was unusual.
The 14
1. Wrong prices — the most common error by a distance
About half of all checkable prices were incorrect. One product was listed at roughly half its real cost; another had its entry tier quoted at about a third. The errors were directional: nearly all of them understated what a buyer would pay.
Catch it: open the vendor's pricing page and read every number, today. Record the date next to the figure.
2. Retired plan names
Several posts named tiers the vendor had replaced years earlier. Even where the number is close, a retired plan name makes the whole paragraph unusable — the reader cannot find what you are describing.
Catch it: copy plan names exactly as the vendor writes them.
3. Free tiers that do not exist
Two products were credited with free plans. Both offer only a time-limited trial. This is the error most likely to waste a reader's afternoon: they choose the tool because it is free, sign up, and discover it is not.
Catch it: read the free-tier limits rather than the word "free".
4. Products that do not exist
Five of them. Two were invented product names attached to real companies — a "Compliance Suite" and a "HIPAA Tracker" that neither company sells. One recommended vendor resolved to a parked domain. One to a domain listed for sale.
Catch it: type the vendor's own domain and look for a page for that exact product name. Ninety seconds. If a product name appears only inside other people's round-ups and never on a vendor's own site, that is the signal.
5. Right product, wrong category
A fitness wearable reviewed as a to-do list app, with deadlines and team assignment it has never had. A transcription platform ranked first among note-taking apps. Both companies are real and well known.
Catch it: read the vendor's own one-line description of itself, then ask whether it belongs in this article.
6. Capabilities the product does not have — and ones it does
We marked a tool down for having "no API for catalogue automation". It sells an API, with its own documentation. That supposed gap was the stated reason for ranking it below a competitor.
Negative claims get checked far less often than positive ones, and they do more damage: you are publishing a reason not to buy something.
Catch it: open the product and confirm each listed feature, including the ones you say are missing.
7. Fabricated first-hand research
Two posts described controlled tests: "we spent 30 hours testing 12 AI photo generators", "we ran 12 identical trials for each tool", with timings to the second. No prompts, no tool list, no date range, no results table. In one, only four of the twelve tools were even named.
Catch it: if a test was run, the dataset ships with the post. If it was not, do not describe one.
8. Statistics with no traceable source
"Reports say", "studies show", "according to a study". Also figures that circulate for years detached from any original — a $2 cost-per-click benchmark traced to a 2017 study of 256 accounts whose actual average was $1.72.
Catch it: open the source and find the sentence. If the number is not in it, the number does not survive.
9. A real source, subtly bent
The most interesting failure. A consultancy's finding that code was written 35–45% faster was restated as "automates 45% of coding tasks". Same study, different claim, and the difference matters to anyone planning headcount.
Catch it: read the source's own sentence, not a summary of it.
10. Anchor text that does not match the destination
A link anchored "predictive analytics tools" pointing at an article about AI image generators. A link anchored "social media presence" pointing at a service selling followers — nothing in the visible text warned anyone.
The strangest: [SKU.As](http://SKU.As), where an auto-linker swallowed a sentence boundary in "saved per SKU. As AI becomes…" and sent readers to a Norwegian municipal property company.
Catch it: resolve every link and read the anchor against where it lands. This one cannot be caught by reading the article.
11. Dead and expired destinations
Links to domains that had expired and now serve registrar parking pages. A citation returning HTTP 410 Gone. A "buy views" page whose domain no longer resolves at all.
Catch it: resolve every link, follow redirects, check the status.
12. Stale platform documentation
A guide to an analytics report that had been renamed, using a navigation path that no longer existed, recommending an attribution model removed nearly three years earlier, and instructing readers to use a product retired in 2023. Its one outbound citation returned 404.
This is the error readers notice fastest, because they are following along as it fails.
Catch it: check anything describing someone else's interface on the day you publish.
13. The article contradicting itself
A "Top 5" containing six entries. A "10 Types" containing twenty-five, with one section duplicated and both numbered 20. A title promising eleven tools over an introduction promising ten.
Why this matters beyond tidiness: an article that cannot count its own sections was not read end to end before publishing, which makes every other error on this list more likely.
14. Guarantees about regulated outcomes
"Ensures regulatory compliance." "Keeps the company safe from fines." "Eliminates the risk of errors."
No software delivers a regulatory outcome. On health, financial or legal topics this is the most dangerous sentence pattern there is — and we published it in healthcare, financial services and oil and gas posts.
Catch it: search your draft for ensures, guarantees, eliminates, prevents. Each one is a claim you have to be able to defend.
What the pattern says
Two things stand out across all fourteen.
The errors are invisible from inside the article. Every one requires leaving the page and opening something else. That is why they survive proofreading, editorial review and quality scoring — all of which assess the text in front of them.
They are worst where they matter most. The fabricated products appeared in a healthcare compliance article. The compliance guarantees appeared in financial services and energy. The wrong prices were concentrated in buying guides. The topics that attract careful readers are the ones that attract careful sourcing least, because they are the hardest to write.
The order to check in
Existence, then category, then price, then capability, then links, then tracking, then statistics, then arithmetic, then platform documentation. Each catches a class the next would waste effort on — there is no point pricing a product that turns out not to exist.
Worked through in full, with the defect each one caught, in nine checks that catch a fabricated round-up.
How This Guide Was Sourced
Written and maintained by the LogicBalls editorial team (logicballs.com). Disclosure: LogicBalls builds AI writing tools. Every error described here is one we found in our own published content.
Method. 530 published posts pulled to local files; 80 reviewed claim by claim on 2–3 September 2026, selected by search impressions. Products checked against the vendor's own domain, prices against the vendor's own pricing page, links resolved through redirects, statistics traced to named sources. Findings from our own review are marked ANALYSIS; vendor wording is quoted with a retrieval date on the individual posts.
On the frequency ordering. This reflects our corpus of 80 reviewed posts, not a survey of the industry, and the "about half" price figure is approximate because some vendors publish no prices at all and cannot be scored either way.
Vendors are not named here. Each correction is published on the article that carried the error, which is where a reader who acted on it will see it. A list of vendors we described wrongly would read as though the vendors had done something.
AI involvement. The posts containing these errors were AI-assisted and published without verification. This post was AI-assisted and reviewed against the audit record before publication.
No LogicBalls telemetry is used in this guide.
Frequently Asked Questions
Are these AI-specific errors?
Mostly no, and that is the point. Wrong prices and stale documentation predate AI. What AI changes is throughput: a model produces plausible, well-formatted, confident text faster than anyone can verify it, so the ratio of unchecked claims to checked ones moves sharply.
Which single check catches the most?
Existence, because it is binary and takes ninety seconds. Price checking catches the most individual errors. Link resolution catches the ones most visible to readers.
How long does verification actually take?
About an hour for a ten-tool round-up, most of it in existence and price checks. The order is what keeps it to an hour.
What if a vendor does not publish a price?
Say so. "The vendor renders prices in the browser and no figure could be read at source" is a legitimate published sentence. Substituting a figure from a comparison site is how stale prices spread.
Does a quality score catch any of this?
No. The posts containing fabricated products scored between 62 and 77 on a 100-point content rubric. A rubric checks whether a citation is present, not whether the subject is real.
Conclusion
Fourteen error types, and thirteen of them are caught by opening something — a pricing page, a product page, a link, a source. The fourteenth is caught by counting.
None of that is sophisticated. What makes it work is doing it before publishing rather than after a reader finds it, and being willing to write "we could not verify this" when that is the honest answer.
