If you ask the big-name consulting firms how to start with AI, they’ll hand you a three-year roadmap. They’ll tell you that before you can even touch the “Send” button on an AI initiative, you have to do three things:
Establish Governance: Build the committee, write the ethics handbook, and ensure every “i” is dotted.
Fix your Data: Spend 18 months scrubbing your database until it’s pristine.
Map the Processes: Document workflows across the organization to ensure total alignment.
Noted. And respectfully, ignored.
The “Boil the Ocean” Syndrome
Don’t get us wrong—Governance, Data, and Processes (and a few other things) are essential. They are the bedrock of a mature, AI-driven enterprise. But if you treat them as prerequisites, you are essentially trying to boil the ocean before you can make a single cup of coffee.
In the time it takes you to “get ready” for AI, the technology will have shifted three times, and your competitors—who were willing to get their hands dirty—will be two miles ahead of you.
Why “Ready” is a Mirage
The truth is, you don’t actually know what Governance you need until you see how AI interacts with your specific team. You don’t know which Data is actually valuable until you try to use it for an automation pilot. And you can’t truly “fix” a process until you see how AI changes the speed of that workflow.
When you wait to be “ready,” you aren’t being careful. You’re being paralyzed.
And “ready” depends on your size, your company and your risks. If you are RBC or JP Morgan (or another global bank) you need “much more ready” than if you are a startup. If you are a mid-size insurer operating in one jurisdiction in one currency with one regulator, you have a smaller need for “data, governance and process readiness.” If you are a tech firm it’s different from restaurant equipment distributor. If you are a startup, it’s different again.
And then there’s the challenge that every new question can require enhancing or building on some previous analysis. You may need more data, or want to explore a new connection.
So the idea of “ready” really isn’t what you need to pursue.
The Adante Approach: Start, Then Steer
We believe in a different rhythm. Instead of boiling the ocean and worrying about hypotheticals, we suggest you start small, start carefully, and fix the “Big Three” as you go.
Governance by Doing: Build your rules around real-world use cases, not hypothetical fears.
Data by Demand: Clean the data that actually moves the needle today, not the data that’s been sitting in a silo for a decade.
Process by Evolution: Map the workflow as you automate it.
This “learn and grow” approach is a much more practical way. Our “Moving the Needle” approach is very project-centred and risk-graduated for this reason exactly. You do what’s necessary and desirable. (See Moving the Needle, or Our Appoach) But not everything imaginable. And that steering is why we say your “AI program needs leadership.” (See Do I Really Need a CAIO? )
The 15-Minute Reality Check
The “Start Slowly” approach doesn’t mean being reckless. It means being intentional. It means picking one high-value area, identifying the specific “Process Mess” or “Data Debt” holding it back, and solving for it in real-time.
At Adante, we have a Five-Question Framework (5QF) that helps CEOs cut through the noise. We don’t need to create a three-year plan. We start with five groups of questions that determine exactly where you can start today to see results next few months.
If you are waiting for the perfect time to start with AI, you’ve already missed the first wave. Stop preparing for the journey and just start driving. We’ll help you navigate the map while you’re behind the wheel.
