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In the last few months I’ve had dozens of conversations with leaders trying to figure out AI. They’ve all been in different industries with different needs but they’ve all hit the same wall..
It’s not people’s ability or budget or tech.. it’s fear.
One leader said it pretty plainly: “Institutional fear is the thing keeping AI out of the building.”
The fear is real, but it's not what you think. It's not that leaders don't believe AI can help, it's that (in their minds) unlocking AI means they have to release their data to the AI overlords.
One manufacturing exec used this metaphor last week.. "Would you let AI plan your vacation if it needed access to your credit card, your loyalty points, and your personal preferences?.. No.” That's kind of what enterprise AI adoption feels like to the people responsible for protecting their company. Every integration and every AI tool feels like a door they’re opening that they’ve spent years protecting.
The irony is that the fear isn't evidence-based. It's really just institutional muscle memory, and it's the single biggest blocker I'm seeing with AI adoption right now.
Here are a few ways we help clients reframe AI adoption to move fast the fear..
1. Start with a highly acute, highly visible problem where AI doesn’t need internal data to solve it.
You don't fight the fear, you go around it. The playbook that's working looks like this:
Start with public or non-sensitive data. Don't touch the stuff that makes your legal or security teams nervous.
Build something highly visible and is an acute pain in a sandboxed environment that doesn't connect to existing systems (i.e., public data).
Put it in front of leadership and let them see the result.
Wait for the question you want to hear.. "What else can we do?"
I've watched this play out in real time with several companies. One industrial company was terrified at the start. We built a tool using only publicly available data, deployed it in a sandbox, and the team launched it externally. They’re viewed as innovators by their leadership and industry folks are paying attention.
AI adoption isn't a technology project, it's a change management project disguised as a technology project. And change management runs on credibility, visibility, and quick wins.
The key is focusing first on a use case that’s a highly acute pain that’s highly visible and uses external data.
2. Reframe AI adoption to “Our people are doing the wrong work.”
Across every conversation, the same pattern shows up. Teams are spending SOOO many hours manually STILL assembling reports/spreadsheets that should take minutes. Folks are STILL buried in email and losing track of tasks. Everyone STILL needs multiple layers of approval just to access their own company's data.
The reframe that works is simple, “Do you really want our best people spending time sending emails and moving things around? Or do you want them serving customers and doing strategic work?”
Focus on getting people time back to invest in higher-value work.
Quick note..
We’re opening the first startup house in Charlotte. It’s a physical space in Southend designed for collaboration/collision of ideas. I’m so stoked to jam with other startups in town! If you or someone you know is building something and want to be in the room, apply here.
3. Reframe AI to “Let’s get new data we don't have yet.”
AI-powered tools don't just answer questions faster, they capture intent signals you've NEVER had access to before.
For example, we recently built and launched an agentic platform for a manufacturing company that allows their B2B customers to easily get answers to technical questions vs searching/sorting/filtering/reading a bunch of docs and PDFs. On the surface, it seems like a simple assistant but the backend/admin for their marketing team is where it gets powerful. They can see who's asking what, when they're asking it to understand customer intent/sentiment, and what patterns are emerging. Connect that to a CRM and suddenly you've got cross-sell and upsell signals based on real customer behavior, not assumptions.
Every AI tool you deploy is also an intelligence-gathering tool. The usage data, the questions people ask, the patterns that emerge.. that's a data set you probably don't have today. And it's often more valuable than the tool itself.
Putting this into action
What's one highly acute, highly visible problem where AI could deliver a quick win? Start there. Use public data, build in isolation, and make the results impossible to ignore.
Stop talking about efficiency gains. Start talking about what your best people could be doing if they weren't buried in manual work.
Whatever AI tool you deploy, add tracking and watch what people do. New sales and marketing opportunities abound 😉
Wrapping up
The companies winning with AI right now aren't the ones with the biggest budgets or the most sophisticated tech stacks. They're the ones who’ve found a sandbox, are building something visible, and turning fear into momentum.
The playbook isn't complicated, the hard part is getting started.
Onward & upward 🤘
Drew
P.S. I hosted a dinner for marketing leaders in Charlotte this month, and the energy around AI adoption right now is unlike anything I've seen. If you're a marketing or CX leader in the Charlotte area and want to be part of the next one, reply to this email. I'd love to have you at the table.
Great time breaking bread with these awesome humans last week 🥂