Artists are the most underused asset in tourism
Artists do more than perform. They absorb, interpret, and reflect the places they move through. In doing so, they create…
AI won’t fix your strategy. But it will expose it. If your audience insight is weak, AI will generate generic messaging faster.
If your positioning is unclear, it will produce “strategy-shaped” language that sounds right—but goes nowhere.
I’ve been thinking a lot about where AI actually helps in the arts—and where it creates risk. This piece unpacks that tension, and why process still matters more than output.
AI is becoming normalized in admin and communications work—and for good reason. It can speed up first drafts, summarize information, and help small teams move faster than ever before.
In the arts, where teams are often lean and under-resourced, that kind of support is hard to ignore.
But there’s a tension emerging that we need to talk about.
AI is making it easier to produce work that looks strategic.
Clear. Polished. Coherent.
And sometimes, completely ungrounded.
A recent report from Work in Culture on AI adoption in the arts highlights the potential for these tools to support administrative and process-driven work. But in practice, the line between “administrative” and “strategic” work is often much blurrier—especially in the performing arts, where marketing, grant writing, and programming all require interpretation, context, and relationship-building.
Treating these tasks as purely administrative risks underestimating the very work that makes them effective.
When organizations turn to AI too quickly, something subtle happens.
If you don’t have a clear understanding of your audience, AI will generate generic messaging faster.
If your positioning is fuzzy, AI will produce language that sounds strategic but says very little.
If your relationships with your community are weak, AI cannot invent them.
So what happens?
You get more output—but not better outcomes.
This is performative competence—work that signals professionalism without being rooted in the insight and process that make it effective.
There’s a tendency to assume that AI is best suited for administrative tasks. And in some cases, that’s true.
But in the arts, many of the things we label as “admin” are anything but.
These are interpretive acts. They require judgement, nuance, and an understanding of people.
When we automate them without doing the underlying thinking, we risk flattening the very things that make our work resonate.
AI introduces a new kind of shortcut—and it’s a tempting one.
Why run a survey when you can ask AI what your audience cares about? Why interview stakeholders when you can generate a strategic plan in minutes? Why test messaging when you can refine it endlessly in a prompt window?
AI is a prediction engine. But the insights that shape strong strategy are often unpredictable. The most important insights come from friction—from conversations that don’t go as expected, from conflicting perspectives, from things that don’t neatly fit a model.
Friction is revealed by:
Some shortcuts don’t save time. They take you in the wrong direction.
The most useful way to think about AI is this: it amplifies what’s already there.
But if those things aren’t in place, AI won’t fix the problem. It might even make it harder to see.
Used well, AI is not a decision-maker or a source of truth. It’s a fast hypothesis generator.
It can help you:
But it still requires a human to ask:
That layer of judgement is where the real work lives.
Most organizations don’t have an AI problem.
They have:
AI just exposes it faster.
And that’s not necessarily a bad thing. Because if we’re willing to slow down where it matters—
to listen more carefully, to think more critically, and to stay grounded in real relationships—then AI can become a powerful tool in service of better work. Not just more work.
The question isn’t just whether to use AI.
It’s whether the foundations you’re building on are strong enough to support it.
