The 6 Organizational Milestones of AI Fluency

Most companies say they're using AI, but only 30% have even created an acceptable use policy. Alane Boyd and Micah Johnson are back with part 2 of their AI fluency series, and this time they're going deep on the organizational level: the six milestones that separate companies dabbling with AI from those actually building with it.

If your team is experimenting with AI tools but you have no committee, no shared systems, and no way to measure who knows what, you're building on sand. This episode gives you the framework to change that, no matter where your organization is starting from.

In this episode, you'll learn:

• How to build an acceptable use AI policy that evolves as your tools and workflows evolve
• Why AI champions matter, and how to identify and use the right people on your team
• How to measure your team's AI fluency using milestone tracking across roles
• The system for sharing wins and roadblocks so AI knowledge doesn't stay siloed
• Why clean data is non-negotiable, and why AI can't fix your messy folder system for you
• How to document your workflows so anyone can understand them, no technical background required

If you're serious about building an organization that doesn't just use AI but grows with it, this episode gives you the exact roadmap. Press play, your team will thank you.

If you haven't listened to part 1 yet, start there first: The 5 Individual Milestones of AI Fluency.

Education & Resources

Claude Cowork Masterclass

🛠️ Tools & Platforms Mentioned

• Claude Cowork
• n8n 
• Slack
• ClickUp
• Asana
• Basecamp
• Skype
• Dropbox / Shared Drive

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Transcript

Alane Boyd (00:05)
All right, this is part two from last week's episode. We're talking about AI fluency on the individual level and the organizational level. And Micah shocked the world, or at least our listeners, whenever he cut us off before we got to the organizational fluency, the five milestones to get there. So we are going to be jumping in today. So if you haven't listened in at part one of this, listen in first and then jump into this one.

Micah (00:35)
So, Alane, I love the intro because it felt so good to know that I shocked three people in the cliffhanger for our last episode. but yeah, so in this week's episode, we're gonna pick up right where we left off organizational track of milestones. Like Alane said, if you didn't listen to last week's episode, check that out first. We introduced this whole concept of AI fluency. How do you track it? How do you measure it?

Alane Boyd (00:40)
Ha ha

Micah (01:00)
And there's two tracks, the individual level and the organizational level. The individual level, we've identified five already. and you may listen to that and go, Well, I wanna add one or I wanna switch it up. Go for it. They're your milestones. On the organizational level, there's six.

Alane Boyd (01:16)
Mm.

Micah (01:17)
Yeah, it's very dramatic. We've gotta make this exciting somehow.

Alane Boyd (01:20)
It is.

I know. All right. Are we ready to jump in, Micah? Or is there anything that you wanted to add before we do that? Yeah, me too. All right. So the first one, it's so simple in theory, is creating an acceptable use AI policy for the organization.

Micah (01:28)
I think I have added enough.

Yeah, and there's stats on this. Only 30% of companies that are using AI have actually achieved this milestone. So this is yeah, yeah. This is a real milestone though. I mean, there's still two thirds that haven't even done this.

Alane Boyd (01:48)
I thought that was high.

It is kind of shocking, but also not shocking. But if you're an organization and you're talking about using AI, start with some type of policy in place, even if it feels basic. What are the approved platforms? What can you put in and not put in? Are you encouraging? I mean, start putting this small stuff in there.

And I I even see our AI policy has evolved, Micah, from when we originally did it, because the platforms that are how we approve platforms, how we use it, things change and we just keep adding to it as this evolves over the last well, for us over the last four years.

Micah (02:22)
Yeah.

I mean, I think there's one truth, and not to get off on a complete tangent, but anything with AI becomes iterative. Improving anything, editing any like everything's iterative these days. And that's so important to remember. One thing that I do want to point out on these organizational milestones too, is they're not as linear.

Alane Boyd (02:43)
Mm-hmm.

Micah (02:54)
As the individual milestone. So the individual milestone, it made sense. You could progress up the ladder if you want to think about it that way or hit these different levels. But organizationally, these are more like check the box. Like, do we have an acceptable use policy? Or the next one, do we have an AI committee that's helping steer what we're doing as a company for AI, helping surface the winds, the roadblocks, what's working, what's not.

What should be standardized? Making all these decisions needs to go through a person or a committee so that you can create less silos and create standardization to build upon and identify your actual AI champions.

Alane Boyd (03:39)
It's so important. You cannot do a good job of rolling any software out. We advocate for this and have since we switched from Skype to Slack, where we have champions, sometimes it's you and I, Micah, but sometimes it's not. Sometimes when you brought Asana to me 12 years ago, you and another person on the team championed it first. It

It helps so much to figure out how the company is going to use it before you mass give it to everybody. Figure out what are some of the standard use cases? What are some of the ways that we're going to use it internally? There are so many ways to use AI and other software platforms. You need to figure out what your company way is. And those AI champions help it. What's that?

Micah (04:22)
So you wanna know what our secret was to sell you on any software lane?

You wanna know what our secret is to sell you on any software?

Alane Boyd (04:29)
I I don't know. Give me a credit card and tell me to go shopping because I'm like never excited.

Micah (04:32)
Ha ha

Yeah, no,

we we share how it's gonna benefit you personally.

Alane Boyd (04:40)
it's much harder than that. That's not sure. We'll go with it. Yeah.

Micah (04:42)
Yeah.

But that opens the door, right? Like if you

can't even understand or see that point of view, then there's no, there's no discussion at all. And this is how it works across teams too. There's a lot of people that go, I don't understand AI. I don't know why I'd use it. I can do it better myself. And until they see or feel the benefit to them personally, they're gonna stay in that mindset. There's no conversation to be had. There's no you can't get past that.

Alane Boyd (04:52)
Mm-hmm.

Mm-hmm.

Micah (05:14)
Because they don't

understand how it helps them. People care about what helps them and benefits them. And once they we see this every day. Once they see, like even last episode, we talked about, you know, in one of our conversations, there's people that will build Skills and Cowork while we're talking about Skills. They try it out and then they're already saving like 45 minutes to an hour with a single Skill that took them five minutes to build. And as soon as they do that, they have converted. They go.

Alane Boyd (05:21)
Mm-hmm.

Micah (05:43)
Okay, I get it. So champions, a hundred percent.

Alane Boyd (05:44)
no.

⁓ I

will say with with this and and and the comment about me and how you win me over with new software, the key really honestly is if we're gonna switch software, great, fine. I'm you know, I can't win all my battles. But if you are a champion and I am not an owner of that championship, meaning I was not participating, I want training on that decision. And that is exactly what we have for our team members.

And I am a huge advocate for that, even internally, is if we're gonna switch software, okay, fine. But we're gonna train our team. If not, it is so painful because then you're reinventing the wheel with every single person. Their learning ability is different. And that's the expectation we're putting on them, and we're moving slow. So my frustration level gets dissolved when we do training, if I'm not part of the champions that puts it in place.

Micah (06:40)
That's

super accurate. Yeah. And it's really smart. All right. So the third one, again, not in any order, but the third milestone is being able to measure the AI fluency of your team. So this directly correlates to last episode. You can measure it by tracking milestones. You identify the milestones. We gave you five ones that you could start out with, but you have to understand where your team is at individually, set a baseline and go from there. Big milestone.

Alane Boyd (06:53)
Mm.

Micah (07:08)
on the organization level.

Alane Boyd (07:11)
It definitely is. And with these, we're talking about them, unrelated to each other. Like you're saying, like it's not a linear process, but they do feed into each other. Your AI champions are gonna help with measuring the AI fluency. It's gonna help you develop your AI policy. and each AI champion is gonna be on their own individual track.

Micah (07:32)
Yep. Absolutely. All right. You wanna take the fourth one?

Alane Boyd (07:37)
Sharing systems.

Micah (07:39)
This is how do we actually share what's working? If I create a Skill, how do we create as an organization the ability for me to feel safe to go, hey AI committee, check out this Skill that I created. I think this would work for all account managers, or I think this would work for our entire marketing team, or I think this could be something that would apply company wide. If you don't have the ability to have your team share.

wins and losses. Then you don't yeah.

Alane Boyd (08:08)
I talk about this a lot because

you can't work in silos. And you're only as good as your next best idea. Well, man, I got 10 smart people on my team. I want to leverage some of their good ideas. And so with that sharing the systems, and that's not even, hey, like this this Skill is available. It's all the hacks. Like we have our team has a Claude Usage Slack channel where we share.

Micah (08:12)
Exactly. Exactly.

Yep.

Alane Boyd (08:36)
Good ideas that we've had and share it with the rest of the team. And we keep learning and evolving with those team members. And it's been amazing.

Micah (08:45)
It also breeds a lot of excitement of like, I didn't know that. I'm gonna try that. And then that becomes a learning moment. Or I'm stuck here and other people can help. So I I ran into that. Like it's Claude will get stuck when you try to update a Skill. Just tell it to show you the Skill and you'll get past that. Brilliant.

Alane Boyd (09:06)
And we have

it it is. And we have different ways of this. And I see, you know, other companies doing other ways. You know, some of them like to do it as part of their weekly department meetings. Some of them like to do it in their leadership meetings that they already have so that they are making it a conversation. Some of them are doing breakout sessions with team members to work through workflows and hey, how could we use Skills or agents to help solve pieces of this work

Micah (09:23)
Yeah.

Alane Boyd (09:33)
flow. Our main way is the Claude usage, but also bi-weekly Claude trainings with our team. So we don't just train during those calls, but we're also, hey, what cool way did you use it this week?

Micah (09:47)
Yeah. Now, milestone five, I think this is one that I don't know that everybody is going to want to hear it, but you need to hear it.

Alane Boyd (09:57)
It's so tough for companies.

Micah (10:00)
And that is you gotta have clean data.

Alane Boyd (10:06)
It really boils to the top when you start putting systems in place and you need a system for using AI that maybe we haven't been doing such a great job. We've kind of got the wild, wild west going on over here.

Micah (10:19)
Yeah, we hear a lot of, well, we've got to make some internal decisions on how we want to handle this.

Alane Boyd (10:27)
Yeah. Maybe there needs to be a centralized database or folder like a Dropbox or shared drive or something like that.

Micah (10:32)
Knowledge store. Yeah. Yeah.

Yeah. And naming conventions need to be important. And a lot of people were hoping that AI could help them solve this. And while it can support in the ability to get to clean data, it still is a you need clean data sources. And that is a huge milestone to become successful with AI.

Alane Boyd (10:56)
Yeah, I mean how you have things saved in your folder system, if you're leaving that to AI to make judgment calls, it's not gonna be as good.

Micah (11:03)
No. Or if you want AI to go through a terribly organized folder system and magically fix it for you, nah, that's not gonna work either. It's oftentimes easier to start with a blank slate and curate data and knowledge into it that AI can access and leave all your messy stuff out in the wherever it is that you have it. Start clean, build it up fresh, and iterate as you go. That's a great way to achieve this milestone.

Alane Boyd (11:25)
Yeah.

Yeah. mean we've done that with software.

I think about when we moved from Basecamp to Asana, we just started new and kept an account for a while and just moved stuff over as we needed. And man, it was so much less of a headache.

Micah (11:42)
Yep, same thing Asana to ClickUp.

Alane Boyd (11:44)
Mm-hmm. All right. Our last one, Micah.

Micah (11:49)
The final milestone again in no order, but it's being able to document your workflows. So what do you have going? How does it work? What's the high level diagram? Being able to actually describe and have anybody in the company go, wait, what what does this Skill do? Is this tying in n8n? Is this connecting to a database? Being able to read one document.

And without any technical knowledge or any background, understand what it does. It's much harder than it sounds.

Alane Boyd (12:22)
It saves your butt though, I'll tell you that. Because when you're wondering, when you're a user especially, and you're like, hey, why didn't this automation run? If you don't have any documentation, the only thing you can do is go have one of the builders go dig in for you and figure it out.

Micah (12:24)
Yeah, it does. Yeah.

And what if they're not at the company anymore?

Alane Boyd (12:44)
Yeah. Well, then you've got another resource that's got to dig in and figure it out. Man, by having that documentation for us, it's like that's our first path. Okay, why didn't it fire? well, that step was actually supposed to be a manual step because we want the human in the loop. That's why it didn't fire and our team missed it. Okay, well, we didn't even have to bother anybody else because we looked at the documentation of the workflow.

Micah (13:09)
Now, if you have individuals that have hit certain milestones, this is one of the things that we actually just covered in a recent cohort. We went over how do you build a Skill in Cowork that can analyze one or more workflows and build this how it works document in seconds, right? And this used to be such a huge knowledge transfer burden.

Somebody builds it, then you got to manually draw a high-level diagram. You've got to write up this document. Ugh, it's just awful. For years and years, that's how we had to do it. Now you feed one or more workflows and Skills into Cowork. You run the Skill to create this document. And the document is created with a high-level diagram for you in the exact proven method that we did. So we shared this with all of our cohort members in this last cohort. And it's

really impressive. Like now anybody can take that Skill in that cohort and go and start documenting their workflows. So there's an easy way. Join our cohort if you'd like to hit milestone six on your organization level and get that one checked off.

Alane Boyd (14:21)
Ooh, nice. So something really comes to like top of mind for me as like a big takeaway from both of these two episodes, Micah. And and the it's the concept that AI is not, I checked the box and it's done. Like I did this one training and now we're using it. It is not. It is an evolution. It is absolutely company and individual milestones because your team is going to be at different stages.

Micah (14:36)
Mm-hmm.

Alane Boyd (14:50)
they need continued support even for us, like we've been evolving how we use Cowork. What you goes into n8n what our AI policy is. Not in any day do we go, okay, we're good. We've checked the AI box.

Micah (14:56)
Yeah.

Yeah. And let me let me throw two more things at you that I would say we even have not put enough effort into thinking through this up until recently, which is I would say we're we're kind of going with the flow and we're flowing with the punches here, whatever. but it's the two things that we also need to take care of or think about from that perspective that you're saying is

Alane Boyd (15:19)
Ha ha.

Micah (15:30)
Today, Cowork, mid-2026 versus mid-2027, 12 months from now. They're releasing so many improvements, so many models, so many changes. Maybe it's not even Cowork maybe it is, but Cowork is gonna look very different in 12 months. Just think it was released mid-January. We're, you know, near the end of June here when we're recording this. It has dramatically changed in six months. Give that.

Double the time. So that means it it is definitely not a check the box kind of situation. You've got to stay on top of, I understood Cowork in 2026. Yeah, well, that was 12 months ago. So being able to keep up with it and say, how do we keep training on this? These are evolving and repeating milestones that are going to happen on the organization level. And that is part of doing business in this era.

Alane Boyd (15:58)
Mm-hmm.

Mm-hmm.

Micah (16:26)
The second piece is turnover. And so with our last episode, we talked about how does somebody go through the different tiers or the different milestones of AI fluency. Well, when you have a new hire, imagine they're starting at zero. They need to understand your AI fluency milestones, starting from milestone one and working up as far as they need to do based on their role.

And then you can start applying, well, what milestone applies to this role and responsibility when you're hiring the new person from the last person that left? ⁓ but those two things keep this so far from being just like check the box on AI that this is an ongoing recurring thing.

Alane Boyd (17:10)
Ooh, so good, Micah. That turnover. And I was just thinking about we for our new employee training, they're pretty much just learning how to use the software that we use and how we use it for their first week and going into their second week as well. Because we assume, even if they have experience, that they are at ground zero, because I promise you there is nuance to how we as a company use it and we don't want to miss teaching that.

Because then they're gonna be constantly trying to catch up when they're working and trying to get their regular work done. And this falls into it.

Micah (17:45)
Yeah.

Yeah. I think we could do a whole episode on that. And that might be our next episode because two kind of teaser use cases on this or examples would be we can have people that come and work for us that say they've used ClickUp before. That does not mean they know how to use ClickUp the way we use it. We can interview and have. Yeah, exactly. Same thing with Cowork. They could have used Cowork before.

Alane Boyd (18:03)
No, I mean that pretty much means they've had an account.

Micah (18:13)
We're using Skills in a specific way. We have specific Skills. They need to know how we use this software and tool as a company, not just can you use it? Okay, cool. you know, you're good. We spend a lot of time on that.

Alane Boyd (18:23)
Mm-hmm.

Yep.

We do. And I'm gonna just keep my mouth shut 'cause maybe we do another episode and I don't wanna give away all the fun things in this episode. So we're we're gonna take a note on that.

Micah (18:41)
All right, let's do a final recap of the six milestones that we've identified on the org level. Do you want to go through them? All right, all right. So finally, get get some spotlight around here. All right. The first one in no order is having an acceptable use policy for AI. Second one is having an AI committee and AI champions to help lead you through all of this.

Alane Boyd (18:46)
Okay. No, you go for it. Making you do some work.

Yeah.

Micah (19:07)
The third one is being able to actually measure your team's AI fluency. The fourth one is being able to create a system of sharing, what works, what doesn't, wins, losses, roadblocks. The fifth one is having clean data to go into your AI and the systems that are being built and the Skills that are being used and the Connectors. And the sixth and final one is being able to document all the stuff that you're building.

Alane Boyd (19:34)
So fun. And Micah, you mentioned earlier the AI Agent Cohort that we have where we teach how to build agents in n8n. And I thought I would let our listeners know if anybody is interested in joining that cohort. Micah teaches it live. It is a four-week course. And there's live teaching and education. And then another day with live office hours where he helps you troubleshoot and get through any roadblocks in creating your agents. And the next one starts July 20th.