AI Writing Tics and Engagement in Knoxville: What the Data Shows

The AI Writing Problem That Isn't What You Think

Scroll through any marketing LinkedIn feed and you'll see marketers confidently declaring that certain phrases signal AI-written content. "In this article..." Bad. Em dashes—terrible. "Not only... but also"—unforgivable. It's a debate we hear constantly from business owners here in Knoxville who want their content to read as genuinely human.

The problem? Most of these declarations confuse stylistic opinion with actual performance data. What counts as "bad writing" is subjective. But what reduces reader engagement? That's measurable.

This analysis examined 1,000+ content marketing pages across 10 different domains to identify which AI writing patterns actually correlate with lower engagement, and which ones are just stylistic hot takes with no real impact on performance.

How We Built This AI Writing Analysis Study

To separate fact from opinion, we built a comprehensive dataset of AI writing patterns and their correlation with reader engagement.

Our dataset included:

• 10 domains of varying sizes and monthly traffic
• Industries: tech, e-commerce, healthcare, education, analytics, and more
• 1,000+ content marketing pages
• Content types: fully human-written, human plus AI collaborative, and fully AI-generated

We standardized the data by:

• Converting all writing tics to occurrences per 1,000 words (longer articles naturally contain more of everything)
• Excluding pages under 500 words (too short to show stylistic patterns)
• Using engagement rate as the primary metric (GA4's "engaged session" equals 10+ seconds of user interaction)

Why engagement rate matters: Engagement rate captures the reader's first real decision: "Does this content feel worth reading?" It's long enough for someone to skim an introduction, notice awkward patterns, and decide whether to continue. It's the real-world equivalent of first-impression quality.

The AI Writing Tics We Analyzed

We tracked 5 specific patterns commonly cited as "AI tells":

1. "Not only... but also" constructions. Pattern: "Not only does X do Y, but it also does Z." Frequency in dataset: very high in AI-generated content.

2. Sentence starts with "then," "this," or "that." Pattern: "Then you should..." "This means..." "That shows..." Frequency: extremely common in AI-generated content.

3. Introductory filler phrases. Pattern: "In this article," "We'll explore," "Let's take a look." Frequency: present in 80%+ of AI-generated content.

4. "Conclusion" starters. Pattern: "In conclusion," "To conclude," "Finally." Frequency: common in structured AI-generated content.

5. Em dashes. Pattern: using em dashes for punctuation and emphasis. Frequency: highest prevalence in the entire dataset.

The Biggest Surprise: Em Dashes Slightly Improve Engagement

When we analyzed the raw data, em dashes dominated every analysis. They're everywhere in the dataset. But here's the shocker: em dashes correlated positively with engagement rate.

Key findings on em dashes:

• Despite being labeled "AI artifacts," em dashes showed a slight positive correlation with engagement
• This challenges the widespread assumption that em dashes equal bad writing
• Likely explanation: writers who use em dashes tend to write more nuanced, explanatory sentences
• These longer, more thoughtful sentences appear in higher-quality content that readers actually engage with

The lesson: em dashes aren't causing engagement, but they're not the content killer everyone claims either.

The Phrase That Actually Hurt Engagement: "Not Only... But Also"

Among all the AI tics analyzed, "not only... but also" constructions showed the strongest negative correlation with engagement.

What we found:

• Negative correlation: -0.15 (statistically significant)
• When used occasionally, these constructions can add emphasis
• When used repeatedly, they trigger reader bounces
• One page in our dataset used "not only" and "but also" 12 times in a single post
• Readers notice the repetition immediately and it reads as mechanical

Why this pattern fails: the construction feels forced and artificial when repeated. "Not only does this technology improve speed, but it also reduces costs. Not only is it affordable, but it also increases efficiency. Not only does it work better, but it also saves time." After 3-4 repetitions, readers start to notice the pattern and the writing feels robotic.

Starting Sections With "Conclusion" Is the Red Flag

The single strongest negative signal in the entire dataset: headers that begin with "Conclusion."

The data:

• Negative correlation: -0.118 (the strongest in the study)
• This is specifically about explicit "Conclusion" headers before CTAs
• Typically appears at the end of pages
• Suggests readers scroll to the bottom quickly and bounce

Why this matters: explicit conclusion sections telegraph the end of content. Readers who scroll directly to the "Conclusion" section are already planning to leave. The header itself signals "we're about to wrap this up." It's a stylistic tell that content is structured mechanically rather than providing continuous value.

The Tics That Don't Actually Matter

Many commonly cited AI writing patterns showed no meaningful correlation with engagement.

"In this article," "Let's explore," "In today's digital landscape":

• No significant correlation with engagement
• Readers don't seem to punish these phrases
• They're common enough in human writing too

Sentence starters like "This" and "Then":

• Minimal correlation with engagement
• Present in both high- and low-performing content

Em dashes (as discussed):

• Slight positive correlation
• Not the content killer they're made out to be

The Control That Changed Everything: Shakespeare

To verify whether our dataset was capturing actual "AI tics" or just common English patterns, we ran the same analysis on two control samples.

A published novel from 2021 (definitely human-written): scored 6.9 AI tics per 1,000 words.

Shakespeare's "Hamlet": scored 11.4 AI tics per 1,000 words.

The conclusion: "AI tics" are just common English prose patterns. Shakespeare scores higher on "AI markers" than most AI-generated blog posts. If Shakespeare had access to ChatGPT, people would accuse him of being too reliant on AI.

What This Means for Your Content Strategy

1. Don't panic about AI stylistic patterns. Most phrases people criticize as "AI tells" don't correlate with reduced engagement. "In this article" isn't hurting your content. "Let's take a look" isn't sabotaging your strategy. Don't rewrite content based on someone's thread declaring certain phrases "AI markers."

2. Watch out for repetitive constructions. The real problem isn't individual phrases. It's overuse of specific patterns. "Not only... but also" used once? Fine. Used 12 times? Readers will notice and bounce. Similarly, "then," "this," and "that" as sentence starters are fine individually but become obvious when repeated.

3. Avoid explicit "Conclusion" sections. The strongest negative signal we found was headers explicitly labeled "Conclusion." Instead:

• Blend conclusions into analysis
• Use subtle transitions
• Add new value before wrapping up
• Don't signal the end with explicit headers

4. Use em dashes appropriately. Em dashes correlate with better engagement. If your writing style calls for them, use them. They tend to appear in more nuanced, thoughtful sentences—which is exactly what performs well.

How to Apply This: A Data-Backed Editing Checklist

Knowing which tics matter is only useful if it changes how you edit. Here is the practical pass to run on any draft, AI-assisted or fully human, before you publish.

• Hunt for repetition, not phrases. Use find-and-replace to count "not only" in your draft. One or two is fine. If it appears four or more times, rewrite the extras. The data flagged repetition, not the occasional use, so do not waste time deleting every instance.
• Kill the "Conclusion" header. This was the strongest negative signal in the study. Rename that final section so it teaches something new, like "What to do next" or a real takeaway, instead of announcing the end.
• Leave your em dashes alone. They correlated slightly positively. Stripping them out, which many marketers now do reflexively, is editing against the evidence.
• Ignore the harmless tells. "In this article," "let's explore," and sentence-starting "this" or "then" showed no meaningful correlation. Spending an afternoon scrubbing them is theater, not improvement.
• Spend the saved time on value. Redirect the effort you would have wasted on cosmetic tics into the things that actually moved engagement: a clearer answer up front, an original data point, a concrete example. That is where the return is.

Common mistake to avoid: editing your content to please the AI-detector crowd rather than the reader. As the Shakespeare control shows, the "tells" everyone polices are just ordinary English. Optimize for usefulness and you optimize for engagement at the same time.

The Bigger Picture: AI Writing in 2026

The obsession with "AI tics" misses the real point. Good writing is good writing, regardless of whether AI assisted in creating it. Bad writing is bad writing, AI or human.

What actually matters:

• Value to the reader (does this answer their question?)
• Clarity (can they quickly understand the point?)
• Originality (does this offer something new?)
• Structure (can they find what they need?)
• Honesty (is this authentic and trustworthy?)

These factors matter far more than whether you used "In this article" in the opening.

Questions About AI Writing and Engagement

Q: Should I remove all em dashes from my content?
A: No. According to this data, em dashes correlate slightly positively with engagement. Use them if they fit your style.

Q: Are certain AI writing patterns actually bad?
A: Only two patterns showed clear negative correlation with engagement: excessive "not only... but also" constructions (overused, reads mechanical) and explicit "Conclusion" headers (signals end of content). Everything else is mostly style preference.

Q: Does Google penalize content for using AI?
A: No. Google doesn't have a penalty for AI-written content. Google cares about usefulness, relevance, and authority. The writing style doesn't matter.

Q: What's the real difference between AI-written and human-written content?
A: The best AI-assisted content is edited and customized heavily. The best human content is original and well-researched. What matters is whether the final content is valuable and honest, not who or what created the first draft.

Q: I'm a Knoxville business owner. Should I worry my content "looks AI-generated"?
A: Worry about whether it is useful, not whether it trips an AI detector. This study found most so-called tells have no correlation with engagement, and detectors are unreliable. A genuinely helpful, locally relevant Knoxville article will keep readers and rank regardless of how it was drafted.

Q: Are AI content detectors accurate enough to trust?
A: Not reliably. The Shakespeare control here scored higher on "AI markers" than most AI-generated posts, which shows these markers are just common English. Making editing decisions based on a detector's score means optimizing for a flawed tool instead of for your reader.

Q: What single edit gives the biggest engagement gain?
A: Removing the explicit "Conclusion" header and replacing it with a section that adds new value. It was the strongest negative signal in the study, and it is a five-minute fix on almost any page.

The Real Lesson: Write for Readers, Not Search Engines or Critics

Content marketers have spent the last year obsessing over whether their content "looks AI-generated." This research suggests that's mostly theater. Most phrases people point to as "AI tells" don't meaningfully impact reader engagement.

What does impact engagement: usefulness, clarity, originality, and honesty. These are evergreen principles that have nothing to do with whether AI assisted in the writing process.

Write content that serves your reader. Avoid lazy, repetitive patterns, whether AI- or human-generated. And stop panicking every time someone on the internet declares that em dashes are the death of content marketing. Because according to the data, em dashes are actually fine.

If you're a Knoxville business that wants content built on data instead of hot takes, our Knoxville design and content team can help you put these findings to work.

Frequently Asked Questions

What are AI writing tics?

AI writing tics are the recurring words and phrasings that signal text was generated by AI, such as 'delve,' 'in today's fast-paced world,' 'it is important to note,' and the overuse of em dashes and three-part lists. Readers increasingly recognize these patterns, which can quietly erode trust in a Knoxville brand's content.

Do AI writing tics hurt engagement?

Yes. Content stuffed with generic AI phrasing tends to feel impersonal and forgettable, which lowers time on page and reader trust. Knoxville businesses consistently see better engagement when an AI draft is edited into a specific, human voice with real local detail.

How do you remove AI tics from content?

Cut filler openers and clichés, replace vague claims with specific numbers and local examples, vary your sentence length, and read the draft aloud. Use AI for the first draft, then edit it heavily so it reads like a real Knoxville expert wrote it.

Is it bad to use AI for marketing content?

No. AI is a useful drafting tool; the real problem is publishing unedited AI output. Google's guidance rewards helpful, people-first content regardless of how it was produced, so editing for accuracy, originality, and voice is what actually matters.

How can Knoxville businesses make AI-assisted content rank?

Make it genuinely useful: answer real customer questions, add first-hand experience, cite credible sources, and strip out generic phrasing. Helpful, specific, well-edited content earns rankings and AI citations, while thin, obviously templated content does not.