Mike Simmons · Catalyst Book a Clarity Call

Skills > Tools

Being ready for AI is not the same as using it.

Using it well is what gets results.

You bought the tool. The CRM. The coaching software. Access to an AI like ChatGPT. And your team still works the same old way.

It looks like the tool is the problem. It usually isn't. What's usually missing is that nobody learned to use it on real work. So that's what we fix. We pick one task, build a working prototype on the AI tool you already have, and hand it back to you working.

Start with one task →

One real task. A working prototype. Built on the AI you already pay for, not ours.

01
Awareness
You understand why AI matters. You already have the tools.
02
Skill
You learn to use it by doing one real task.
03
Execution
The task gets done without you. The way your team works actually changes.

Being ready is step one. Using AI well is step three.

95%

95% of company AI projects don't help the bottom line at all. Only 5% actually do. The difference isn't the tool. Everyone is using the same ones. The difference is that the top 5% learned how to use them. Being ready isn't the same as using it well.

Source: MIT Project NANDA · The GenAI Divide: State of AI in Business 2025

What's Probably Happening

You bought the tool. You expected people to work differently. They didn't.

So the obvious next thought is: "I bought the wrong tool." Time to shop for a new one. A better platform. A different vendor.

Before you spend more money, consider this. It isn't a criticism of you or your team:

The tool showed up before your team had the skill to use it. And nothing else changed to make that possible.

Why This Happens

The order matters: mindset, then skillset, then toolset.

A tool only helps once your team already has the skill to use it. Buy the tool first, and it just sits there. People keep doing things the old way.

First
Mindset

What are we actually trying to solve? And do we believe in it?

Then
Skillset

Can your team actually do the work? Have they practiced it?

Only then
Toolset

Now point the tool at work your team is ready to do.

Readiness training and "AI readiness" checklists are useful. They build a foundation, the skills and knowledge your team stands on. But they still aren't the same as actually using AI well.

And this isn't just our opinion. Notion's 2026 study of more than 6,000 leaders and workers across ten countries found something telling: the more advanced a company gets with AI, the wider the gap grows between buying AI tools and knowing how to use them, climbing from 48% of leaders saying so up to 68%. And at the most advanced companies, the single biggest thing slowing them down is a skills gap, bigger than trust, rules, or technical problems. The tool arrived. The skill to use it never caught up.

Using AI well means your team works differently. That's where the results live. Getting there right matters more than getting there fast.

A Note to Leaders

First, understand how AI actually got into your company.

Before your team can use AI well, you need to know how it got there. It usually happens one of three ways, and each one raises questions people often forget to ask:

Way 1
You upgraded to Copilot, or something like it.

How was it set up? What company data can it see? Did your IT team actually customize it for your business, or just turn it on? And are you good with that?

Way 2
You installed AI on your own servers.

It's connected to your systems, but closed off from the internet. Do you have a written AI policy? Rules for who can access it? A plan for when something goes wrong?

Way 3
You approved AI tools team by team.

Who's paying for what? Which tools are allowed and which aren't? Where does the data come from, where does it go, and who is allowed to build automated tools with it?

These are just a few of the questions worth answering before your team can really succeed with AI. Answering them, writing the policy, training your team on it: that's readiness, and it's real progress. It builds the foundation your team stands on.

Readiness is part of the journey. It just isn't the finish line. We help you go the rest of the way, one task at a time.

Proof This Works

I've done this myself.

7
Apps shipped
25+
Custom GPTs
8
Projects

Every single one was built for one real task, using tools I already had. Not a test lab. Not a big rollout. One task at a time, until I no longer had to do that task myself. I used AI to take work off my own plate that my team used to do by hand.

One of those tools has since been shut down, because the task it did changed. So I retired it, kept what I learned, and stopped maintaining something I no longer needed. Knowing when to stop using a tool is just as important as knowing when to build one. Most people only tell you what they added, not what they let go of.

That's exactly what we do with your team. We don't say "get ready for AI." We take apart one real task, build something that actually does it, and hand it back to you working.

25 years of doing this kind of work.

UPS Microsoft Intel MIT O'Reilly Disney

Who This Is For

This is for you if either sounds familiar.

You have this
You bought tools, and nothing changed.

You made the call. You signed off on the budget. You expected things to work differently, and they didn't.

You care about the people
You care about a team that's stuck.

They're working just as hard for the same results. Maybe burning out. And you know buying another tool won't fix it.

It doesn't matter what your title is: revenue leader, operations leader, or just the person responsible for the people. What matters is that this is your problem to solve.

How We Work Together

We build one thing, and then you don't need us for that task.

Step 1
Pick one task

We choose one real task and break down exactly what it involves, the decisions and the steps underneath it.

Step 2
Build a working version

On the AI tool you already have. We test whether it actually does the task, not whether it looks good in a demo.

Step 3
Improve it with real feedback

We test it on real work and real edge cases until it holds up outside the demo.

Step 4
Hand it off

You keep a working tool that takes that task off your plate, or your team's.

Start with one task →

We figure out the first task on a short call. Your tools, your data, your task.

What You Get

What you walk away with.

Not a readiness plan. Not a slide deck. Something that actually runs, on the tools you already pay for.

Start with one task →

Currently booking 1–2 weeks out

You don't need another tool. You need your team to actually use the one you have.

That starts with one honest conversation about what's really stuck.

In that same Notion study, the fastest-growing complaint from companies is "we have too many AI tools," climbing from 11% to 25%. Buying another platform was never going to fix that.
Start with one task →