Free Resource

Are you actually ready for AI?

10 questions every business should be able to answer before spending a dollar on AI tools or consultants. Takes 5 minutes. See your score instantly.

Enter your email to unlock the checklist — we'll also send you a copy to keep.

The AI Readiness Checklist

Check every item that's true for your business right now. Your score updates as you go.

I can name one process that costs us 5+ hours a week and runs on clear rules.

AI replaces repeatable logic. If you can't name the process, you need an audit before you need a tool.

I know where our key data lives and it's accessible.

AI needs inputs. Scattered spreadsheets and locked systems are a data problem before they're an AI problem.

My team has bandwidth to implement something new in the next 60 days.

AI adoption takes attention upfront. A stretched team will stall any rollout regardless of how good the tool is.

I can define what success looks like in 90 days — specifically and measurably.

Not "improved efficiency." Something concrete. Without a target, you can't evaluate results or build buy-in.

One person on my team owns the AI initiative.

Shared ownership is no ownership. Someone needs to be accountable for rollout, metrics, and adoption — or nothing ships.

We have budget allocated for tools, not just time.

Free tools rarely solve business-critical problems. If leadership hasn't committed budget, you're set up for a "we'll do it later" conversation.

Key stakeholders agree on why we're doing this.

Misaligned executives kill more AI projects than bad technology. If your team has different theories about the goal, fix that first.

We have a way to capture when something isn't working.

AI systems need feedback loops. Without a mechanism to flag errors, you silently accumulate them.

I've had an honest conversation with my team about what AI means for their roles.

Teams that feel blindsided resist. One transparent conversation does more for adoption than any training program.

We're willing to start small, learn, and iterate — not launch and declare victory.

The companies that win treat AI like infrastructure: incremental, tested, adjusted over time. The ones that fail treat it like a product launch.