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The Secret Behind Colgate's 51% AI Adoption Rate (And What Your Team Is Missing)
While tech giants are tying AI usage to performance reviews and threatening employees with termination, a 220-year-old toothpaste company is quietly running one of the most successful AI adoption programs in corporate America.
Colgate-Palmolive. Toothpaste. Speed Stick. Ajax. Hill's Pet Food.
51% of its white-collar workforce uses advanced AI tools weekly — not just clicking "rewrite" in Gmail, but running deep research, building AI assistants, writing code. That number has grown every quarter. And they got there without a single mandate, performance penalty, or ultimatum.
The contrast with how most companies are handling this couldn't be sharper.
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TLDR: Most companies are forcing AI adoption and making it worse. Colgate built a culture of AI curiosity instead — and the results are lapping the industry. Here's what they did differently, what the data shows about why forcing it backfires, and a prompt to help you audit your own team's AI readiness.
Why the "Mandate" Approach Is Failing
Here's what's happening across corporate America right now:
Meta became the first major technology company to formally tie employee performance reviews to AI usage in February 2026, making "AI-driven impact" a core expectation for every employee. Google, Amazon, and Salesforce followed with similar policies.
The instinct makes sense. The execution is backfiring.
A study of nearly 14,000 workers across 19 countries found that while regular AI usage jumped 13% in 2025, worker confidence in the technology plummeted by 18% in the same period. "Workers are being handed tools without training, context, or support," the researchers concluded.
The result? Employees who are technically compliant but functionally checked out. They use AI enough to avoid scrutiny. They don't use it well enough to create real value.
Between 78% and 86% of employees now use unapproved AI tools at work — not occasionally, but regularly. They're routing around their company's official tools because the official rollout gave them nothing to work with.
🧴 What Colgate Did Instead
Kli Pappas, Colgate's global head of AI, didn't send a mandate. He went looking for tinkerers.
He walks the halls of Colgate's New York and New Jersey offices searching for employees already experimenting with AI — then turns them into internal evangelists. Twenty-four "AI ambassadors," one per major business unit, each managing ten more within their departments. Curiosity spreads person to person, not top-down by policy.
When an ad agency tried to dismiss AI with outdated examples, Pappas didn't argue policy. He took over the screen share and showed them what a current model could actually do.
The result at a manufacturing plant in Athens tells the story cleanly: equipment kept breaking down because repair manuals were in German, French, and English — but workers spoke Greek. A plant manager built an AI assistant to translate and answer questions in real time. Machines got back online faster. Colgate expanded the tool to 43 manufacturing sites globally.
That's not a mandate producing compliance. That's a problem getting solved — and spreading because it worked.
📈 The Gap Nobody's Talking About
Only 10% of the American workforce uses AI daily, despite 45% saying they use it at least a few times a year. The casual users aren't getting the productivity gains. The daily users are.
54% of business leaders believe their companies will not remain competitive beyond 2030 without AI adoption at scale — yet most of them are trying to close that gap through pressure instead of pull.
Colgate's playbook inverts this. Pappas measures quality of use, not just frequency. Clicking the rewrite button in Gmail doesn't count. Running deep research in Gemini does. Using ChatGPT to build a custom assistant does. Solving a real operational problem does.
The bar is higher. The motivation is intrinsic. The results compound.
💬 The Prompt: Audit Your Team's AI Readiness
Whether you're leading a team or thinking about your own role, this prompt helps you assess where the real gaps are — and what to do about them.
You are an AI adoption consultant helping a business professional
honestly assess their team's or organization's AI readiness.
Ask the following questions ONE at a time. Wait for each answer
before moving to the next. Then provide a specific, honest assessment
with 3 actionable recommendations.
Questions:
1. What's your role, and how large is the team or organization you're thinking about?
2. On a scale of 1–5, how would you rate your team's current AI usage —
1 being "almost nobody uses it" and 5 being "it's part of daily workflow"?
3. What's the #1 reason people on your team resist or avoid AI tools?
4. Does your organization currently measure AI adoption? If so, how?
5. What would "success" look like to you — what would change about how
your team works if AI adoption doubled?
After all 5 answers, provide:
- An honest assessment of where the team sits on the AI adoption curve
- 3 specific, practical steps to increase adoption through curiosity,
not pressure — tailored to what you heard
- One "quick win" they could implement this week
Frame everything around building capability, not enforcing compliance.
We ran this prompt with a real scenario to show you what comes back.
The profile: A department manager. Team of about 15. A few people experiment with AI occasionally, but most don't. No measurement in place. Goal: just get more done.
What AI diagnosed:
📍 Stage: "Early Curiosity" — a few explorers, no shared momentum yet
🚧 Core problem: People don't see clear use cases for their specific work, so AI feels like extra effort, not a shortcut
📊 Missing signal: No one has shown the team what "good use" actually looks like
The 3 recommendations it gave:
🗓️ Use Case Fridays — 15 minutes a week, one person shares a real prompt they used, what it saved them, and the actual output. Peer proof beats policy every time.
📋 A 5-task AI playbook — Document five tasks where AI helps immediately (drafting emails, summarizing docs, turning notes into plans). Include the exact prompt and an example result. When people can copy a proven prompt, confidence rises fast.
⚡ Reframe learning as shortcuts — Instead of "learn ChatGPT," say "paste this before writing your next report." If AI feels like a cheat code, not a course, adoption accelerates.
The quick win for this week:
Run a 30-minute session. Show three use cases. Have everyone try one prompt on their own work. Then ask: "What would save you the most time if AI could do it?" Most teams surface 2–3 high-value workflows on the spot.
No mandate. No performance review pressure. Just a clear path from curiosity to capability — which is exactly what Colgate figured out first.
🗞️ Quick Bites
META NOW GRADES EMPLOYEES ON AI USAGE — AND PAYS BONUSES UP TO 200%
"AI-driven impact" is a formal metric in Meta's 2026 reviews.
Engineers are tracked on how many lines of code they write with AI assistance.
Colgate's Kli Pappas would call this the hard way.
────────────────────────────────────────────────────────────────
ONLY 7% OF COMPANIES TELL EMPLOYEES HOW TO USE TIME SAVED BY AI
Per a Gartner survey of 114 HR leaders, almost no one has answered
the most basic question of AI rollout: "If AI saves you two hours —
what should you actually do with them?"
The companies winning at AI adoption aren't the ones with the strictest mandates. They're the ones with the best evangelists.
Find yours.
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