Why people write emails with AI

The most common use cases: sales teams using AI to personalize cold outreach at scale, recruiters drafting job descriptions and candidate messages, support teams generating first-draft replies, and professionals drafting formal correspondence faster. The output ranges from lightly AI-assisted (a human wrote most of it) to fully generated (the human changed nothing).

Knowing the difference matters in several contexts: you received a sales pitch and want to gauge whether anyone actually thought about you, a job offer email feels off, you are reviewing whether your team's outreach sounds human, or you are in a professional context where authenticity matters.

The phrase patterns that give it away

AI writing assistants consistently reach for the same vocabulary. These phrases appear at much higher rates in AI-generated emails than in human correspondence:

Openers

›“I hope this email finds you well”
›“I hope this message finds you in good spirits”
›“I trust this email finds you well”
›“I wanted to reach out to you today”

Closers

›“Please do not hesitate to reach out”
›“Feel free to reach out if you have any questions”
›“Looking forward to hearing from you”
›“I look forward to the possibility of connecting”

Transitions

›“With that said”
›“That being said”
›“Moving forward”
›“In light of the above”

Filler qualifiers

›“As a valued customer”
›“In today's fast-paced environment”
›“In today's competitive landscape”
›“It goes without saying that”

No single phrase confirms AI authorship. Humans write "I hope this finds you well" too. The signal is density: two or three of these in one short email is unusual for a real person but routine for GPT-4.

Structural tells

Beyond vocabulary, AI emails tend to share a recognizable structure:

Perfect paragraph structure

AI reliably opens with a hook or context sentence, follows with 1-2 supporting sentences, and closes with a call to action. Human emails meander, skip sections, or end mid-thought. An email with clinically correct paragraph structure across 5+ paragraphs is worth a second look.

No typos or informal contractions

Humans type "its" when they mean "it's", skip words, use fragments, and sometimes write "imo" or "tbh" in informal contexts. AI doesn't. A long email with zero errors, zero informal language, and no autocorrect artifacts is unusual in most business contexts.

Generically personalized

AI-generated outreach often includes a reference to something specific about you (company name, a recent product launch, a LinkedIn post) but then pivots immediately to generic pitch language. The personalization is surface-level: one sentence that could have been filled in by a template, followed by text that could go to anyone.

Symmetrical bullet points

If an email includes a bulleted list, AI typically produces items of very similar length and grammatical structure. Human-written lists are messier: some bullets are fragments, some are full sentences, lengths vary significantly.

Polite hedging everywhere

Phrases like "I believe", "I think you might find", "it may be worth considering", and "you might want to" cluster in AI emails because models are trained to avoid strong claims. A human salesperson would not hedge this much; they would say "this will help you" not "I believe this might potentially be helpful".

What AI detectors can and cannot do with email

Detection tools like Airno run AI probability analysis on any pasted text, including email. Paste the body of the email (subject lines are too short to be meaningful), and the tool will return a confidence score.

A few caveats specific to email:

Short emails are harder to score

Detection models have less signal to work with in 3-sentence emails. Confidence intervals are wider. A 5-sentence email returning 65% is worth noting; it is not worth acting on alone.

Formal professional writing scores higher than it should

A human writing a formal business email to a CEO will naturally use elevated language that detection models associate with AI. False positive rates are higher for formal correspondence. Use the score as one signal, not a verdict.

Heavily edited AI drafts score lower

If someone generated an email with GPT-4 and then edited it substantially, the final version may score closer to human. The detector is measuring the output, not the process.

Detector scores on email are probabilistic

A 78% confidence score does not mean 78% of the words came from AI. It means the ensemble of detectors collectively estimates a 78% probability that the overall email was AI-generated. That is meaningful but not a binary determination.

How to read the Airno breakdown on an email

When you paste an email body into Airno, you get a score from each of the seven detection models. For email specifically, pay attention to:

Pattern

This detector scans for 190+ AI phrases. For email, look at the 'ai_patterns' sub-score. A high pattern score on a short email is more meaningful than on a long document, because the phrase density is higher.

Statistical

Measures perplexity (how predictable the word choices are) and burstiness (whether sentence length varies like human writing). Very low perplexity in a short email is a strong signal.

Syntactic

Analyzes sentence structure variation. AI emails often have very similar syntactic structures across all sentences, which shows up as low syntactic diversity.

A worked example

Subject: Exciting Opportunity to Connect Hi [Name], I hope this email finds you well. I wanted to reach out because I believe our solution could add significant value to your organization's operations. In today's fast-paced business environment, staying ahead of the curve requires leveraging the right tools. Our platform provides seamless integration with your existing workflows, empowering your team to achieve more with less effort. I would love to schedule a brief 15-minute call to discuss how we can help. Please do not hesitate to reach out if you have any questions. Looking forward to connecting. Best regards, [Name]

This email contains: "I hope this email finds you well", "I wanted to reach out", "add significant value", "In today's fast-paced business environment", "staying ahead of the curve", "leveraging the right tools", "seamless integration", "empowering your team", "Please do not hesitate to reach out", and "Looking forward to connecting." Ten phrases from Airno's AI pattern database in ten sentences. The pattern detector alone would return a near-maximum score.

A human sales rep might write two or three of these phrases in a rush. Ten in one email, with perfect paragraph structure and zero casual language, is not how people write when they are actually thinking about you.

What to do with the information

If you are on the receiving end of a suspected AI email:

01Sales outreach: Knowing it is AI does not automatically mean the product is bad. It means the sender chose volume over personalization. Factor that into how seriously you take the message.
02Job offers or recruiting: A fully AI-generated offer letter is not necessarily a red flag about the company, but it is worth asking whether a real person reviewed it before sending.
03Reviewing your own team's output: If your support or sales team is using AI assistants, run samples through detection periodically to see how human (or not) the output reads. High scores mean customers may notice too.
04Legal or compliance contexts: Some regulatory environments require disclosing AI use in communications. Detection is one input into that audit process, not a definitive answer.

If you are writing AI-assisted emails yourself

The phrases listed above are easy to remove once you know them. A quick pass through any AI-generated email to cut "I hope this finds you well", "please do not hesitate", and "looking forward to connecting" will drop the AI signal substantially.

The structural tells are harder to fix by editing. If you want email that reads as genuinely human, the most effective approach is to use AI for the first draft and then rewrite at least half of it in your own words. A detector score is a useful quality check before you send.

For an honest measure of how your outreach reads, paste it into Airno before it goes out. A 30% score means you sound like yourself. An 85% score means your customers probably know.

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