The AI Readiness Checklist

The Training Gap (By the Numbers)

Companies that invest in AI training alongside tools see much higher adoption than those that just buy the tools.

The pattern is clear across every industry: teams that get structured training adopt AI within months. Teams that get a login and a "figure it out" adopt almost nothing.

Most business leaders say their teams need AI skills. Almost none have actually started training them. The tool is never the bottleneck. The people are.

This checklist helps you figure out where the gaps are before you spend another dollar on AI subscriptions.

Leadership and Strategy

AI adoption starts at the top. If the people in charge can't explain why you're using AI and what good looks like, the rest of the team won't know either. Check each box that's true for your business.

• We have a clear reason for adopting AI (not just "everyone else is doing it")
• Leadership can explain what AI should do for the business in plain, specific terms
• We have a budget allocated for AI training, not just AI tools
• Someone is responsible for AI adoption (it's not "everyone's job")
• We've identified 3-5 specific workflows where AI could save time
• We have a timeline for rolling out AI (not "sometime this year")

Tools and Infrastructure

Having the right tools matters, but only if people can actually use them. This section checks whether your setup is ready for real use, not just a line item on a budget.

• Our team has access to at least one AI tool (ChatGPT, Claude, Gemini, etc.)
• Everyone knows how to log in and has used it at least once
• We have guidelines for what data can and can't be shared with AI
• Our AI tools integrate with the systems we already use (email, CRM, project management)
• We've thought about whether we need chat-based AI (like ChatGPT), automation tools (like Zapier or Make), or both
• We have a process for evaluating new AI tools before buying them

People and Skills

This is where most businesses fall down. The tools are there. The skills aren't. If your team doesn't know how to use AI well, it doesn't matter how much you're paying for subscriptions.

• Team members can write a basic prompt that gets a useful result
• At least one person knows how to write good prompts (instructions for AI) beyond the basics
• The team knows when to use AI and when not to (judgment, not just capability)
• People feel safe experimenting with AI (no punishment for slow adoption)
• We have internal examples of AI saving time that we can share
• Training is scheduled, not just "available if you want it"

Processes and Workflows

AI works best when it's built into how your team already works. Random one-off use won't make a real difference. Regular, planned use will.

• We've mapped our most time-consuming repetitive tasks
• We've picked out which tasks AI could help with (the repetitive, follow-the-rules, high-volume ones)
• We have a way to measure time saved or quality improved
• AI outputs are reviewed by a human before going to clients or customers
• When AI gets it wrong, we have a way to learn from it and improve next time
• Automations are documented so the team understands how they work

Scoring Your Results

Count your checked boxes out of 24 total. Find your range below.

What to Do Next

You've got your score. Now turn it into action. Here are four steps to take this week.

• 1 Pick the 3 unchecked items that would have the biggest impact
• 2 Assign an owner and a deadline to each one
• 3 Schedule a team training session (even 60 minutes makes a difference)
• 4 Revisit this checklist in 30 days