How to make sales emails sound less AI when your SDRs draft with AI

Your reps are using AI to draft outbound. Fine. The problem is that prospects have now read a lot of it, and a certain kind of email gets deleted fast. It isn't that the grammar is wrong. It's that nobody seems to be home.

This page is for SDR managers and reps who want AI's speed without the tell-tale sound. It covers a workflow you can run on every draft, a worked before/after, the objections worth raising, and where this approach won't help.

What makes an outbound email sound like AI

It's rarely one word. It's a stack of small habits that show up together:

• A warm-up opener. "I hope this email finds you well" or "I came across your profile." It says nothing and every recipient knows it.
• Praise with no object. "Impressed by your work at [Company]." Impressed by what, exactly?
• Abstract benefit language. "Streamline workflows," "drive efficiency," "optimize outcomes." No noun a person could point at.
• Even rhythm. Every sentence is about the same length, and every paragraph has three beats.
• A tidy, over-polite ask. "Would you be open to a quick 15-minute call to explore synergies?"

We keep a longer list in words that make writing sound like AI, and a general method in how to make AI writing sound human.

Why it matters for SDR teams specifically

A blog post that sounds generic gets skimmed. A cold email that sounds generic gets deleted, or reported as spam. That second outcome is the expensive one.

Google's sender guidelines tell senders to keep the spam rate shown in Postmaster Tools below 0.10% and avoid ever reaching 0.30%. One deliverability write-up points out that the spam-rate guidance applies to all senders, not just those sending over 5,000 messages a day. At the 0.30% line, that's three complaints per thousand delivered messages. A team sending templated-sounding mail to people who never asked for it can get there faster than you'd think.

We can't tell you that AI-sounding copy directly causes complaints. Nobody has a clean number for that. The reasoning is simpler: people report mail that feels mass-produced and irrelevant, and AI-flavored filler is one of the quickest ways to feel that way. Fixing the sound is cheap. Fixing a damaged sending domain isn't.

A five-step workflow for every AI-assisted draft

1. Put the real reason in the prompt first

Before generating anything, the rep writes one plain sentence: why this person, why now. A job posting, a product launch, a comment they made, a gap on their site. If the rep can't write that sentence, the email shouldn't go out. No rewriting tool fixes a missing reason.

2. Generate short

Ask for under 90 words, no greeting filler, one question at the end. Long drafts have more places for boilerplate to hide.

3. Run the draft through the checker

Paste it into Plainspoke and look at which phrases and patterns read as machine-written. The point is to see the specific lines, not to chase a score. There's more on this format on the cold email page.

4. Rewrite the flagged lines with something only the rep knows

Swap each flagged line for a concrete detail, a specific number from the prospect's world, or just a shorter sentence. Humanizing works best as a first pass. The last 20% should be the rep's own voice.

5. Read it out loud, then send

If you wouldn't say it to someone at a conference, cut it. This catches what tools miss.

Worked example: before and after

The prospect and company below are invented for illustration. This is not a customer example, and we're not claiming any reply-rate result for it.

Before: a typical AI-assisted first draft

Subject: Streamlining your carrier onboarding strategy

Hi Dana,

I hope this email finds you well. I came across your profile and was impressed by your impressive work at Brightline Freight. In the fast-paced world of logistics, optimizing carrier onboarding is crucial. Our innovative platform helps teams streamline workflows and drive efficiency. Would you be open to a quick 15-minute call next week to explore how we can help?

After: same offer, rewritten

Subject: Carrier paperwork at Brightline

Hi Dana,

Brightline has three carrier-ops roles open right now. When that happens, onboarding is usually the bottleneck, not hiring.

We make a tool that handles the paperwork side: insurance certificates, W-9s, authority checks. If that's a live problem for you, I can send a two-minute walkthrough. If it isn't, say so and I'll stop.

What changed

Notice what a tool could not have done here: the line about the open roles. That came from a human looking at a careers page for thirty seconds. The checker's job is to show you the filler. The rep's job is to replace it with something true.

Objections SDR leaders raise

"We already have AI personalization in our sequencer."

Keep it. Merge fields and generated first lines are inputs. They still produce the patterns above, so an editing pass after generation is a separate step. If you'd like to see how we differ from other writing tools, the comparison pages go through them one by one.

"Isn't this just fighting AI detectors?"

No. Your audience is a buyer with a crowded inbox, not a detection model. Detectors also flag plenty of human writing, which we explain in why AI detectors flag human writing. Write for the reader and the detector question mostly goes away.

"Won't this slow reps down?"

It adds a step, so yes, a little. The trade is fewer, better emails per rep instead of more, worse ones. If your model depends on raw volume, this workflow will feel like friction, and you should be honest with yourself about that.

"What about our prospect data?"

Check what you paste in. Read our privacy policy before putting prospect details into any tool, ours included. A good habit is to edit the draft with placeholders for names and then fill them in.

Where this won't help

• Bad targeting. A perfectly human email to the wrong person is still spam.
• Deliverability setup. Authentication, unsubscribe handling and sending reputation are separate work. Google's guidelines cover them, and no writing tool replaces that.
• Missing research. Without a real reason to write, you'll just get a smoother version of generic.
• Enforcement inside your sequencer. If you need a hard gate on every send, a writing checker is an editing step you run, not a policy engine. Look at how you'd build that into your process before you buy anything.

Try it on your worst-performing sequence

Take the email your team sends most often and run it through the steps above. If the result reads like something a colleague would write, you've got a template worth keeping. Start with a draft or check pricing first. For LinkedIn follow-ups, the same logic applies and we cover it on the LinkedIn page.

Sources

• support.google.com/a/answer/81126
• www.allegrow.co/knowledge-base/google-bulk-sender-guidelines
• www.warmy.io/blog/email-deliverability/gmail-bulk-sender-requirements-explained/

Check a draft free