Starting to fold AI into your sales org's workflow is like a first kiss.
It's an awesome, terrifying, confusing start of a new chapter — one that can go horribly wrong if you don't know what you're doing.
The difference is that you can just Google "how to kiss" and be in a decent spot with that.
Org-wide AI adoption has a steeper learning curve, so we surveyed over 300 sales leaders on where they're at with AI adoption to help make it a little less imposing.
Teams who've AI across most of their workflows may have built on a dirty foundation.
Our survey found:
25%
of sales leaders say AI is scaled across most of their teams' daily workflow.
10%
say they cleaned our audited their data before deploying AI for outreach.
All six letters in the word "scaled" are pretty mission critical, but for this conclusion, we're really going to focus on the letter "d".
When sales leaders say, "We've scaled AI across our workflow," it means they're treating it as a done deal: infrastructure is in place, reps aligned, results compounding.
25% of our respondents say that's the case in their orgs. However, only 10% say they've cleaned or audited data before deploying AI for outreach.
That indicates that "fast on adoption — slow on foundation" is a prevalent pattern, and many orgs build AI outreach workflows on shaky grounds.
Data readiness should be treated as a precondition, not a parallel workstream on this front.
AI running against outdated, un-audited data isn't scaling. It's amplifying the mess.
Top reps are compensating for infrastructure their orgs haven't built.
Our survey found:
26%
of first place votes went to "a rep researches before reaching out" as the #1 differentiator for top-performers (the top response).
13%
of orgs have a defined data process or cadence everyone follows.
Several organizations aren't building systems to scale the habits that set top reps apart.
26% of our respondents say their best reps distinguish themselves with how they "research before reaching out, not during." 23% say they do it by "keeping their own accounts clean and current."
However, only 13% of organizations have a defined data process or cadence that everyone follows.
Many of those top reps are compensating for an unsound data infrastructure with personal discipline. That's a gap worth sitting with.
If those reps were in better-structured environments, they wouldn't have to distinguish themselves by compensating for systems that aren't there.
If you can systematize those habits, you can close the gap between top and average.
What can you do with this next-level insight?
For reps:
The reps most burned by AI output share a pattern: they treat it as ready to send. A lightweight verification habit — checking contact currency, confirming account context, reading for tone — changes the error rate materially without meaningfully changing the pace.
For managers:
Reps who miss on targeting usually aren't less hardworking — they lack a defined, communicated standard for what "ready to contact" looks like. Establishing that standard as a team-level expectation changes the floor for the whole group, not just the ceiling for the best performers.
For leadership:
The habits that most separate top reps from the middle — research discipline and account hygiene — are buildable, not innate. Leaders who operationalize those habits into the motion itself stop waiting for the right people to show up and start raising the floor for the people already there.
Mike Tyson once said, "It's the truth, I'm the best. And I'm just convinced, you know what I mean? These fellas, how dare they challenge me with their somewhat primitive skills. They're just as good as dead."
That's a perfect encapsulation of how I feel about the broader sales newsletter community.
I can't relate to 100% of the things Mike Tyson has said — but I feel that one.
Jay Fuchs. Managing Editor, The Science of Scaling Newsletter
94% of sales leaders say their teams are using AI. Which sounds like progress, until you ask whether it's actually working.
HubSpot talked to over 1,000 sales and revenue leaders to learn more.
The State of Sales in 2026 report looks at what’s driving pipeline today.
Where buyers are pushing back. And what the gap looks like between teams that are ready for the AI era, and teams that just think they are.
The data in question
As always, we sourced our data through Panoplai: It's so freakin' good. You have no idea how good it is.
Where is your team with AI in the sales motion today?
- 28% — We haven't deployed AI in our sales workflow yet
- 25% — It's scaled across most of the team's daily workflow
- 25% — It's deployed in pockets, but not consistently across the team
- 22% — We're piloting it in a few places.
Before leaning on AI or automation for outreach, what did your team do to get ready?
- 25% — Started small and expanded once it worked
- 20% — Set rules for what AI can and can't act on
- 18% — Trained reps on when to trust it vs. override it
- 15% — We're not using AI for outreach
- 12% — Nothing specific — we turned it on and adjusted
- 10% — Cleaned or audited the data first
Rank what separates reps who consistently reach the right people from those who don't. (ranked, top 3 — first-place votes shown)
- 26% — They research before reaching out, not during
- 23% — They keep their own accounts clean and current
- 21% — They act fast on buying signals
- 16% — They lean on tools the rest of the team doesn't use
- 14% — They know who else to involve in the account
How does your team keep contact and account data current today?
- 24% — A mix — different parts of the team do it differently
- 23% — Reps update records as they go, by habit
- 21% — A dedicated person or ops team owns it
- 13% — A defined process or cadence everyone follows
- 13% — An automated tool handles it
- 6% — Honestly, it doesn't stay current