AI isn’t coming for your job. It’s coming for your excuses.

I’ll be honest: I dragged my feet on AI. I can remember a few years back, a colleague of mine telling me I should jump on the bandwagon to sell "AI enablement for agencies."

At the time, that sounded ridiculous. Not only was technology new, but I hadn't even written a single prompt. I passed and said it wasn't for me because I don’t have time to learn another thing that’s changing every five minutes. Plus, I’ve been doing this long enough to know that every few years, something shows up and promises to change everything. Most of it doesn’t.

Two years later, I can say this one does.

Over the past few months, I’ve been writing, experimenting, and honestly just paying attention. AI isn’t just speeding things up; it’s changing how work gets done, what deliverables look like, and how teams interact. When it’s used well, it pushes thinking. When it’s not, it just makes mediocre work faster.

If you’re trying to figure out how AI actually fits into agency work, you’re not alone. What’s become pretty clear to me is that AI isn’t hard to use; it’s just hard to use well. And yet, I keep talking to agency leaders who are still circling it, debating it, or waiting for someone else to figure it out first. That might feel responsible, but it’s also a great way to fall behind without realizing it. Because the market has already moved. Budgets are shrinking, teams are leaner, timelines are tighter, and expectations didn’t magically get lower to compensate. AI doesn’t solve any of that, but it does change how you deal with it—and whether you can keep up without burning out your team.

The real challenge isn’t AI. It’s us.

This is where things get uncomfortable. Because this isn’t just about tools or workflows, it’s about people and how they feel about the work.

In almost every team, there’s a divide. You’ve got the early adopters trying everything, pushing boundaries, seeing what sticks. And then you’ve got the holdouts—the ones who don’t want to touch it. Not because they can’t, but because they don’t trust it. It feels like a shortcut, or worse, a threat to the craft.

And honestly, I get that. Part of me still feels that way. I care deeply about craft, about original thinking, about not turning everything into the same polished, average output. There’s a real fear that AI flattens the work, and in the wrong hands, it absolutely does.

But ignoring it isn’t the answer either. Whether we like it or not, this is the environment we’re working in now. And the teams that figure out how to engage with AI—thoughtfully, critically, without losing their standards—are the ones that will keep up without burning out.

So a big part of the work right now isn’t forcing adoption. It’s unlocking curiosity, and helping people move from resistance to experimentation, or even from fear to understanding...from “this is going to replace me” to “this might actually help me do better work.”

What creative teams actually need to adopt AI (hint: not another tool)

Most teams don’t need another list of AI tools. That’s usually where things go wrong.

What they actually need is a way to engage with AI without blowing up everything that already works. They need a shared understanding of where it genuinely helps and where it quietly makes things worse. They need guardrails that protect the quality of their thinking and the integrity of their work. And maybe most importantly, they need permission to experiment without feeling like they have to get it right the first time.

That’s the gap I’ve been focused on closing.

Recently, I had the chance to design and facilitate a two-day AI workshop focused on AI adoption for a creative agency. The goal was to help the team figure out how AI actually fits into the way they work—across disciplines, in real projects, with real constraints.

The workshop: making AI real (not theoretical)

This workshop wasn’t all about specific tools or prompts. My intent was to open up the conversation, inspire curiosity, welcome debate, and land on solutions that feel right for the business, as well as the culture.

We spent two days looking at AI from every angle—where it helps, where it falls short, and where it raises real ethical questions around originality, ownership, and trust. Not in theory, but in the context of actual work. That’s where things got interesting.

In some team experiments and discussions, it was clear that AI sped things up or unlocked new ways of thinking. In others, it felt completely unnecessary, like using AI to solve a problem that could be handled more thoughtfully with a simple template or a clearer process.

That tension is the point. It forces teams to think more critically about how they work. Where the value actually is. What should be automated, and what absolutely shouldn’t be.

It also brings up something more personal: what parts of the work people actually enjoy, and what they’re willing to hand off. Because the goal isn’t to strip the work down to its fastest possible version. It’s to protect the thinking, the craft, and the parts of the work that make it meaningful while using AI to reduce friction, speed things up, and support better outcomes.

Used that way, AI doesn’t replace the work. It changes where you spend your energy.

What happens next

The workshop wasn’t the end goal. It was the unlock.

It opened up what’s possible with AI, but it also made things more complicated in a good way. Now there are real questions to answer: What’s our stance on AI as a company? How do we talk about it with clients? Where does it actually belong in our process, and where does it not?

Clients aren’t just curious about AI anymore; they expect it. And once they know you’re using it, it becomes a convenient reason to shrink budgets without lowering expectations. So we’re left doing more with less, again.

The only way that works is if we get smarter about how we spend our time. AI can handle the obvious, repeatable parts of the work so we can stay focused on the thinking, the creativity, and the decisions that actually matter.

But none of that works if the team isn’t bought in.

This isn’t something you mandate. It’s something you have to build into the way people think about their work. People need to see the value for themselves. They need to feel comfortable experimenting, asking questions, and figuring out where it helps them, not just where leadership says it should.

That’s the real next step. Creating space for curiosity, across disciplines, so teams can make better decisions together and use AI in a way that actually improves the work, not just speeds it up, but actually makes it better.

T L ; D R - AI isn’t hard to use—it’s hard to use well. The real challenge isn’t the tools, it’s helping teams stay curious, protect their craft, and figure out where AI actually adds value. Start small. Use real work. And don’t let speed replace thinking. Also, hire me for a workshop! ;)