Have you told your team to start using AI?

Have you written one of those “It’s Time to Embrace AI” memos to your team like we’ve seen go viral from Shopify, Duolingo, or Box?

How has that gone for you?

Best laid plans…

While everyone knows they should be using AI, changing behaviors is hard.

And learning a new skill and technology that’s unlike past generations of tools is even harder.

Yet, too often, founders and executives think they can just order their team to do it, and magically everyone will embrace AI and get all the benefits we hear hyped online.

I recently worked with a client helping them improve their AI adoption. There I saw even smart, capable people weren’t using AI very often beyond some basic questions to ChatGPT. I learned the real problem isn’t awareness nor desire; the reality is it comes down to problems like time, uncertainty, and trust.

Today’s post breaks down what worked (and what didn’t) in helping a team move from curiosity to consistent AI use, and gives you practical approaches to apply to changing the AI culture at your team, whether you need to get everyone, or a slow adopter or two, on board.

The Real Barriers to AI Adoption

Before we talk about solutions, it’s important for you to understand the problems. Only then can we really get the outcomes you want.

Here are the 3 biggest barriers I noticed that prevented an otherwise talented, hard working team from using AI the way the CEO desired. Many of these will probably be familiar to you and your team:

1. Time and Cognitive Overload

If your schedule is already packed, and you’re hustling hard to get everything done at work, “learning AI” feels like a tax on your day. This is particularly common at high performance startup cultures where AI wasn’t natively part of your business from the start.

Most people don’t even know where to begin, so it’s easier to keep doing what’s familiar.

AI experimentation competes with “just getting stuff done,” so it always loses unless you lower the effort it takes to try.

2. Inexperience and Early Frustration

The biggest killer of momentum isn’t fear. It’s failed attempts.

When you pick the wrong tool, or hit a dead end after getting 60% of the way to what you need, you will likely give up and then go back to what you were doing before…but now 3-4 hours behind.

When you hit early frustrations and blockers, it’s understandable if you then feel gun-shy next time; it makes sense to stick to simple, straight-forward tools (like ChatGPT for writing) and avoid anything that feels riskier, harder, or uncertain. It’s just not worth the lost time, and expended energy.

3. “When in Rome…”

Nothing is more powerful than the example you set. Employees follow what leaders do, not what they say.

Of course, this applies to AI, too.

If your CEO doesn’t use AI, but wants everyone else to, you’re not going to make a lot of progress on AI adoption.

And even if leaders are using AI, they often don’t talk about it enough, which to an employee is the same as not using it.

That’s why the power of repetition matters. Leaders must show and tell, over and over, exactly how you’re using AI to make your work better, so your team sees you value it, and know you’re walking your talk. Otherwise, your repeated encouragement to use AI will simply feel like hollow nagging.

Yet, repeating what you’re doing is barely scratching the surface on how to actually drive AI adoption at your company. So let’s dive into the specific tactics you need to put into practice to get your team to start using AI more.

How to Actually Get AI Adopted Inside Your Company

I am sorry to report that there is no “Easy Button” for boosting AI adoption inside of your company. However, there are some relatively simple and straightforward tactics that can make a big difference.

The key is to recognize that all of these tactics work best in tandem with each other; the sum of all (or most) of these approaches being implemented at your company compound and reinforce each other to truly drive the adoption and behavior change you want.

If you’re a leader trying to change just your team or department, you may not be able to do all of these, but I encourage you to use your creativity to apply as many as you can.

And if you get stuck, I bet your favorite chat-based AI can give you some ideas to try as well…

Tactic #1: Lower the Barrier to Entry

Have you ever tried to use Claude Code? Many people rave about the amazing mini apps, prototypes, task management tools, daily journals, and other systems they built with it.

Yet, if you open Claude Code, it’s far from something that can just build the perfect thing for you out of the box. It requires coming up the curve, a decent amount of trial and error, and some guidance from a friend, taking one of the many online courses, or watching a few Youtube tutorials.

That’s why the last thing you want to do is buy Claude Code subscriptions for your whole team, and just hope they figure it out.

Instead, you want to make it easy to get started. You can help teach them how to use AI by doing things like:

Give your team ready-to-use examples & templates.

Don’t make your people start from scratch. Look for opportunities to provide pre-made workflows, prompts, and automations. These can come from online tutorials you’ve found (I enjoy How I AI, Peter Yang’s content, and many random things I find on X/Twitter), things you’ve tried yourself, or what you’ve heard from peers.

But it’s not all on you. Look for people on your team and in your company who are AI fanatics. They’ll be thrilled to have the chance to share what they’re learning and some of their favorite tips and tricks, too.

Create a shared library as you go.

While sharing some read-to-use templates can help people start, the key is to keep the momentum going. That means creating a reference library for these first few examples, and then continuing to grow the list.

Over time, encourage and recognize your team members for adding great examples to it. Everyone on your team will approach AI a bit differently, so you may be surprised by all the unique ideas that start appearing there.

The key is to put it somewhere easy to find, so use your best judgment on location (i.e. – Slack, Notion, Google Drive, etc).

Highlight low-effort, high-impact use cases.

It’s true that sometimes a master can do a month’s work in a matter of a day or 2, but that’s not where your team is at today. And too often the people going viral bragging about what they’re doing are hiding the fact that they have a CS degree and a lot of coding experience.

To help your team build momentum, look for quicker wins they can experience now. Highlight things they can do with their job and skills to save 2 hours, or turn a 30 minute job into a 3 minute task, not a monumental shift that includes learning about unit tests, evals, and deploying to git.

The easier the win, and the more of them you can stack up quickly, the more positive momentum you can quickly build across your team.

2) Make It Visible: Lead by Example

Nothing will more quickly derail your efforts to drive AI adoption than your team not seeing you and other leaders using AI yourselves. Failing to adopt AI will build resentment in team members, and make them say, “well, if they’re not doing it, why should I?”

But this isn’t just about the downside. The truth is, your example is also the greatest motivator for your team. Here’s what you can do:

Build a habit of sharing your AI use cases

The most important thing you can do is talk openly about how you use AI. As I already mentioned, you should repeat yourself often: in Slack, at all-hands, in team meetings, and in 1 on 1s.

Hopefully you have different use cases to talk about over time, but the key is that your team keeps hearing you talk about AI, and digging into how exactly you are using it and getting real, tangible value.

Share other people’s use cases, too

It’s not all on you. I know you have a job beyond being an AI evangelist in your company. That’s why you should also be sharing other people’s work, both directly (tell your team about it) and indirectly (invite others to share their examples).

You can accomplish this through a few different tactics:

• Include “AI show-and-tell” segments in your meetings, so anyone adopting AI and getting value can share it with everyone else.
• Host lunch-and-learns where leaders and employees share experiments, or invite guests who can show and tell what they’re doing, too.
• Have your team post their “AI wins”. When you spot one at work, tell your team member to post about it. They won’t always think to do it, and you’ll have more visibility across your team than most so take advantage of what some of your early adopters are doing.

The key is to treat these as routines; you don’t do them once and you’re done. Instead, it becomes habits and rituals that are as normal a part of your culture as going over the latest metrics.

3) Incentivize the Right Behaviors

So far we’ve talked a lot about the “How” of getting your team to adopt AI. It’s important to know what to do and how to actually get value without getting discouraged or slop results.

Yet, to truly bring behavior change to your team, you also need to think about incentives. In this case, you’ll want to use both the proverbial carrot and stick to get the results you want.

The Carrot 🥕

You best motivate people based on what you praise and reward, which is why we’re focusing on it first. There are quite a few easy, straightforward ways to provide carrots (positive incentives) for your team to use AI more.

Some tactics you should practice regularly:

• Publicly recognize and praise people using AI creatively in meetings, in chat, and anywhere else you know people will see.
• Add an “AI Uses” part of your company meetings, and make it a reward to get to present during that time.
• Offer spot bonuses, rewards, and public shout-outs for great AI uses, especially if they save time, or make your company more money.
• Create a lightweight internal award (e.g., “Prompt of the Month”).

The key is to have fun with it. Do things that fit your culture, while avoiding things that your team thinks are cringe, or that make the person uncomfortable (i.e.- some people don’t like public praise, preferring instead to hear it from you privately).

The Stick 🔨

Unfortunately, not everyone hears other people getting praised, or sees those positive rewards and responds well. That’s why you also need consequences for those lagging behind.

Fortunately, there are fair and reasonable ways to do that, which give people some time to catch up, or plenty of forewarning before you need to do something more drastic (like a performance improvement plan).

Here’s some tactics you can use:

• Make AI usage part of their performance review. If there is a section to evaluate when and how much they use AI, that will get any tech laggard’s attention.
• Tie raises and promotions to AI usage. If people realize that their chances at advancement are tied to AI, that will motivate your ladder climbers quickly.
• Keep AI in mind when staffing. Whether you tell teams they can’t hire until they prove AI can’t do the extra work that needs done (like Shopify has), or you consider whether you need to backfill a role or can automate much of it with AI, staffing requests are a helpful choke point for checking how your team’s adoption is going.

The key with any of these incentives is communication. As a leader, it’s your job to tell your team about any new factors you’ll be evaluating their performance on way before review time. And it shouldn’t be a surprise for you to tell a team they can’t add additional headcount, because you want them to try to use AI to do it first.

Or put even more simply: Sticks only work if people know the stick exists and it’s enforced.

Other Incentive Ideas

You don’t have to only rely on direct punishment or rewards to help drive adoption. There are other incentives you can use to make it easier and more likely your team will use AI.

These include things like:

• Give your teams an AI budget. This can be helpful in multiple ways: you can require people to demonstrate how they’re using the tool, thus teaching everyone about the use case. You can also then use the lack of usage of the budget as a sign someone isn’t adopting AI and needs some nudging or coaching by you.
• Create a team leader board tracking AI usage. Shopify famously shared in their First Round Capital article that they track AI credit usage, praising employees using AI the most. Can you make an equivalent on your team? (and can AI help you quickly create it!?)
• Tie AI adoption metrics to departmental OKRs. If AI is supposed to allow us to do more faster, measuring that impact is a great way to turn skeptics into believers. You can also consider making learning AI a development OKR for everyone on your team, so they know it’s a priority.

As Charlie Munger famously put it, “Show me the incentive and I’ll show you the outcome.” That’s as true for AI adoption as it is anything else, so if you haven’t consider your team’s incentives, it’s time to review this section and choose the ones that fit you best.

You don’t need to apply all of them, but if you don’t have *any* incentives, don’t be surprised if your adoption feels slow.

4) Build a Learning Culture Around AI

To really cement the adoption of AI at your company, it’s important to keep people learning and growing. There are new trends, use cases, and abilities happening frequently, so you really can’t rest on your laurels, even if you start seeing more usage.

To keep up, you always need to be learning.

Yet, you can’t do it alone. You could spend all day, every day researching and trying tools, reading and watching what others are doing, and you’d still not capture everything.

That’s why it’s essential to build a learning culture into your team. As a collective, you’re much more likely to keep up on what matters most, and you’ll be well positioned for your team to all adopt the best, most applicable uses of AI team-wide.

Here’s a few rituals and habits you can follow that complement the examples we’ve already shared:

Have a Weekly Show-and-Tell

If there is an empty slot staring at you each week that needs filled with something AI-related, you and your team are much more likely to talk about it. Whether that’s a separate meeting, a few minutes at the beginning or end of an existing one, or you simply have your team member post a loom, they all can work depending on your culture.

The key is that you can use this strategically:

• Highlight a great use case you heard from a team member. (i.e.- “That’s great! You should share this with the team in our AI Spotlight”)
• Rotate presenters so people have positive pressure to find something worth sharing. (i.e.- “It’s your turn next week. What do you want to share?”)
• Talk about what doesn’t work, too. Not every AI experiment is a winner, and there should be no shame in that happening on your team. By sharing some duds, you also open the door for team members to help each other if they know what to try so they get better results.

That last point is particularly important; no AI tool works perfectly every time. It can be educational, and sometimes funny, to see the mistakes AI makes, while also figuring out how to get a better result next time.

Team-Based Learning

Learning AI doesn’t have to be all single player. Your team members aren’t all on separate islands using AI.

You can make the process of learning and adopting AI easier (and more fun) by having your team learn to use it together.

You can try things like:

• Pairing people up to try new tools or work on a project using AI together. They can then help each other when they get stuck, compare notes from their own experiences, and share knowledge.
• Ask your best AI people to hold office hours. This gives your team a dedicated time to ask them question, so they’re not peppering them with questions all day, every day.

Sometimes it is better (and less expensive) for people to learn on their own, so it’s up to you to determine the best mix of people working solo or together. Calibrate based on your company, culture, and experience.

Hackathons

Lack of time to learn AI is one of the most common complaints you’ll hear from some resistant team members. A great way to solve this problem is to give them a large block of time all at once in the form of a hackathon.

The key is to give them a bit of structure like this:

• Make them recurring. Can you spend a few hours one Friday a month? Put it on everyone’s calendars so they can plan for it.
• Give them structure. It’s not free time, nor is it time off. Make your hackathons have expected outputs that everyone shares like:
  • What they tried (ideally with a demo or Loom of the results)
  • What worked and didn’t (lessons learned)
  • What they’d recommend to others (the best prompts, tools, and takeaways)
• Set aside budget. A hackathon may burn through credits quickly if an AI tool is used heavily. Make it clear they can use budget for this, and then like we mentioned earlier, monitor it for positive and negative signals.

These can take a bit more effort up front to coordinate, but then it becomes pretty easy to repeat with minimal tweaks based on what you see working or not.

5) Operationalize the Habit

If you’re trying to change the AI culture of more than just your team of individual contributors, then you need to think about how to make this more broadly applied at your company.

You can take a lot of what we just talked about, but then organize it and scale it up. That can include things like:

• Train your managers on what you want done. Remind them to praise new AI tactics discovered and shared, make clear the carrot and stick changes, etc.
• Maintain a living “AI Inspiration Library”. Have Ops or your Chief of Staff build one out with examples, templates, and top prompts organized by team and use case. Teach your team how to contribute.
• Check all of your internal comms to see where AI should be added or included like weekly recaps, all hands meetings (and recap notes), dashboards, etc.
• Make AI a core part of your employee onboarding. You can do this a few different, and powerful ways:
  • Use AI tools in the onboarding process itself. It can help in countless ways to save you time and do more with less effort.
  • Teach new hires the company’s AI expectations and resources from day one; they aren’t indoctrinated in old cultural habits yet, so they can help bring change to your more entrenched team members.
• Encourage regular “workflow audits” (e.g., hiring, reporting, customer support) to identify automation opportunities, starting with the most common then branching to less common but costly ones.

The key with all of this is that you’re building a company-wide mindset that you should always ask, “How can AI help me do this?” The more experienced and comfortable everyone gets, the more natural that becomes, and the more ROI you will all get from embracing AI.

You can Create a Culture Where AI Becomes the Default

The truth is, there is a lot that goes into building a team or company culture that embraces AI and gets great value from it. While your team has to do a lot of the learning themselves, the actions you take as a leader make all the difference.

Success in this area requires an “all of the above” approach: you must lead by example, create new incentives, commit time and budget, and build in a great deal of repetition and reinforcement.

And you need to be patient.

Culture shifts one behavior at a time, and one bought in employee at a time. You can’t just send one memo and hope everyone listens.

The good news is that the rewards for your efforts and persistence are completely worth it; they allow you to zoom ahead of your competition, and stay there. They prevent you and your team from falling hopelessly behind both personally and professionally.

Because the truth is, AI isn’t coming for your job, but someone who has mastered AI is.

That means by mastering AI, you’re not just helping your company, you’re also setting up you and your team for stronger careers going forward. You will all be in demand, and capable in this ever changing world of AI.

Need help improving AI adoption at your company?

If you’re looking for help getting your team to better adopt AI, or need a product leader that’s thinking AI first, while always keeping the customer and data at the center of their decisions, I’m open to full time and fractional opportunities.

Get in touch here, or schedule time you prefer to talk here.