🤖 AI prompting: An underrated differentiator? (new data)

Many (if not most) modern sales reps shape their outreach with AI.

Their messages generally land on a scale from "I sense a slight robo-influence," to "Zero people talk like this — so no, I will not be hopping on a call."

Regardless of where you fall on that spectrum, your AI-backed outreach probably has room for improvement.

That's why we surveyed over 300 sales leaders for their insight on the subject.

Here's some of what we found.

There's a generic messaging epidemic, and lazy prompting structures are part of the problem.

Only 17% of respondents' orgs shape messages with detailed, structured prompts, and 29% cite generic output as their main AI-backed outreach issue. That's eight points higher than the next most popular option.

That 12-point gap could indicate a pronounced connection between unsophisticated prompting frameworks and vague, sloppy messaging.

A wise man once said, "AI-backed outreach only goes as far as your prompting can take it."

Okay, that "wise man" was technically me, and I "once said" that quote for the first time just now — but it's still true.

An effective AI-backed outreach strategy scales volume without undermining value. Investing in prompting guardrails, reference materials, and training sets the foundation for that.

A reliable, repeatable prompting framework can make detailed prompting straightforward, allowing for higher-volume, thoughtfully targeted, lower-touch personalized messaging.

Reps need to stay on top of the human side of AI-backed outreach.

What can you do with this next-level, revelatory insight?

For reps: Independently experiment with and refine more sophisticated prompting for outreach. If your team doesn't have reference points for prompts that resonate with prospects at a high volume, try to develop some of your own.

For managers: Provide your team with prompting guardrails, reference materials, and templates to enable high-volume personalization. Offer structure that removes the friction from detailed prompting, making quality AI-backed outreach scalable across your entire team.

For leadership: Establish training frameworks for human judgment development in AI outreach. Skills like research, context gathering, and critical evaluation are essential to an effective AI-backed outreach strategy — so don't just proliferate tools without addressing those elements.

"I wrote this newsletter, and I don't care who knows — but if I'm being real, I'd like a lot of people to know."

Jay Fuchs. Managing Editor, The Science of Scaling Newsletter

The data in question

We sourced the data we used here through Panoplai: The panoramic research platform God would have made if he pursued consumer research instead of creating the universe. 

What's the biggest challenge your team faces when using AI to write sales emails?

- Generic output — emails lack the personalization prospects are receptive to - 29%
- Weak prompting skills — reps don't know how to write effective prompts that produce quality results - 16%
- Brand/voice misalignment — AI-generated emails don't match our sales methodology or tone - 16%
- Context inefficiency — we can't efficiently feed AI the information needed for quality output - 16%
- Compliance concerns — leadership worries about accuracy, brand risk, or regulatory issues with AI content - 10%
- None of the above - 21%

How does your organization primarily identify burnout risk before it becomes turnover?

- Detailed structured prompts — specific context, constraints, tone guidance, and desired outcomes included - 17%
- Clear but simple prompts — prospect details and desired tone without extensive structure - 29%
- Basic descriptive prompts — explaining what we want without additional guidance - 18%
- Inconsistent approach — each rep has developed their own prompting method - 11%
- Still experimenting — haven't established best practices yet - 15%
- None of the above - 11%

What skill development priority matters most for your reps to succeed with AI-powered email outreach over the next two years?

- Advanced prompt engineering — knowing how to extract quality output from AI tools - 15%
- Research and context gathering — finding the insights that make emails resonate - 21%
- Critical evaluation — assessing and refining AI output to match quality standards - 21%
- Strategic thinking — knowing when deep personalization matters vs. scaled approaches - 17%
- Technical fluency — understanding AI capabilities and limitations across tools - 16%
- None of the above - 11%