AI Adoption for the Skeptical
A contact in the mining industry recently shared something fascinating with me: "I've got this client, they've always been anti-tech, but now they feel they need to do something with AI."
This is happening everywhere. Industries that spent decades perfecting their healthy skepticism of technology vendors are suddenly worried they're missing out. And honestly? That skepticism might be their biggest advantage.
Here's what I've learned: The companies that succeed with AI aren't the ones making headlines. They're not spending millions on "digital transformation initiatives" or hiring armies of consultants to build proof-of-concepts that gather dust.
Instead, they're asking better questions:
Where do our engineers waste hours searching through old reports?
Which compliance tasks eat up days but follow predictable patterns?
What knowledge is walking out the door when our veterans retire?
The $75K Pilot Beats the $2M Transformation
Big consultancies will tell you AI requires fundamental transformation. New systems! New processes! New everything! (New invoices!)
But generative AI actually works pretty well with your existing mess. Those thousands of PDFs collecting digital dust? That equipment manual from 1987? The handwritten inspection notes? Modern AI can (probably) read all of it.
You don't need perfect data. You need a specific problem.
Start Where It Doesn't Hurt (Much)
The best entry point? Read-only applications. Let AI search and summarize before it creates. Think of it as hiring a really fast intern who's read every document your company ever produced:
"What were the soil conditions in Block 7 in 2019?"
"Show me all safety incidents involving conveyor belts"
"Which permits mentioned groundwater contamination?"
Nobody's job is threatened. Nothing breaks if it's wrong (if you actually read what the AI digs up, of course). But suddenly, answers that took hours take seconds.
The Trust Ladder
Once people see AI finding information faster than their best document wizard, you can climb the ladder:
Search (no risk, high value)
Summarize (low risk, saves time)
Draft (medium risk, human reviews everything)
Integrate (only after proving value)
Most valuable applications never need to go past step 3. And that's fine.
Why Traditional Industries Have an Edge
That "anti-tech" instinct? It's actually perfect for AI adoption. You won't fall for hype. You'll demand ROI. You'll ask uncomfortable questions about what happens when it hallucinates.
Your skepticism forces vendors to prove value early on, not only after a big transformation for $2M. Your caution means you'll start small, fail fast, and scale what works.
The mining executive who said, "We need to do something with AI."? They're right. But that something should be specific, measurable, and boringly practical. Leave the moonshots to companies with venture capital to burn.
What's the most annoying document search in your organization? That's where your AI journey should start.
