How to Write AI Content That Doesn't Sound Like AI

AI language models are trained to be helpful and inoffensive, producing a distinctive style: long hedging phrases, excessive caveats, generic examples, and a fondness for 'furthermore', 'it's worth noting', and 'in conclusion'. Technically correct but reads like a committee wrote it.

The fix is specific. Not 'write naturally' — that's useless advice. Specific techniques that replace the patterns AI defaults to.

AI defaults to generality because it's always true. 'Many businesses struggle with X' is safe. 'A B2B SaaS company with 20 employees typically struggles with X because of Y' is more useful and more credible.

Every time you see a vague placeholder — 'some companies', 'various tools', 'in many cases' — replace it with a real number, a named example, or your own experience.

AI content reliably includes an introduction that re-states the title, a conclusion that re-states the introduction, and a FAQ section that re-states the body. Start with the answer instead.

AI avoids taking positions because positions can be wrong. But readers trust sources that have opinions. Say 'I use Tool X over Tool Y because of Z' rather than 'both tools have their merits'.

WebEnture's AI Content Detector scans your pages for patterns associated with low-quality AI content: repetitiveness scores, filler phrase density, specificity markers — so you can identify which pages need the most editorial attention.