# How to spot AI-generated content in 2026: the em-dash and 8 other tells

> How to spot AI content in 2026: the em-dash is the canonical tell, but it is one of nine. Here is the full diagnostic: eight more vocabulary, structure, and rhythm signs of AI writing, two common false positives, why you should not stop using em-dashes to dodge detection, and the byline-removal test that catches the rest.

URL: https://voicemoat.com/blog/em-dash-ai-tell

## Key facts
- Published: 2026-05-12
- Category: AI and Voice
- Read time: 13 minutes
- Author: VoiceMoat team
- Publisher: VoiceMoat
- Topics: How to spot AI content; AI writing tells; Em-dash AI tell; Detect AI-generated text; Signs of AI writing in 2026

## Key points
- Should you stop using em-dashes to avoid looking like AI?

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## FAQ
Q: How do you spot AI-generated content in 2026?
A: Look for the em-dash first: two or three in a short post is a strong signal. But it is one of nine tells, so read for the cluster. The others are the AI vocabulary cluster, the symmetric two-clause hook template, the not-just-X-but-Y frame, the beige bullet middle, the generic closing CTA, symmetric paragraph rhythm, voice-flat coherence, and missing taboos. Taken together they reveal AI writing in about 30 seconds.

Q: Why is the em-dash the canonical AI tell?
A: The major language models deploy the em-dash as a default rhythm tool at a rate that no normal writer matches, showing up mid-clause, mid-sentence, and mid-list where a comma or period would do the same work. The pattern appears across Twitter, LinkedIn, blogs, and email regardless of topic because it is a model-level habit, not a writer-level choice. Two or more in a sub-100-word paragraph sharply raises the odds the writing is AI-assisted.

Q: Should you stop using em-dashes to avoid looking like AI?
A: No, and this is the most common overcorrection of 2026. The em-dash is a centuries-old mark good writers used long before language models existed. The tell is never the single mark, it is density layered with the rest of the cluster. Amputating a punctuation mark you actually use to dodge a detector makes you read more generic, not less artificial. The goal is to sound like yourself, not to pass a stylometric checklist.

Q: What is the byline-removal test?
A: It is the single most reliable check: remove the byline and ask whether you would still know who wrote it. If yes, the writing carries voice signals strong enough that no current-generation LLM could produce them without a voice-trained workflow. If no, the post is either AI-drafted or written in a register so generic the AI-versus-human distinction barely matters. It captures the real question, which is whether the writing belongs to a specific person.

Source: https://voicemoat.com/blog/em-dash-ai-tell
Site overview: https://voicemoat.com/llms.txt. AI usage policy: https://voicemoat.com/ai.txt.