If you work in visitor attractions, you’ve probably felt it… That low hum of anxiety every time a new headline lands. “Something Big is Happening,” wrote AI founder Matt Shumer in an essay that went viral earlier this year. “The people paying for the best tools, and actually using them daily for real work, know what’s coming.” Then came Citrini Research’s “2028 Global Intelligence Crisis”, a fictional dispatch from two years in the future, painting a world where AI hollows out white collar work so fast the economy can’t absorb the shock. It rattled Wall Street enough that Citadel Securities published a formal rebuttal with Fed data in hand.

The fear is real. And in an industry that already runs on tight margins, seasonal staffing and institutional knowledge held in the heads of people who’ve been doing this for decades, in one still recovering in many corners from the pandemic… it hits different.

So let’s name it: you’re wondering whether AI is coming for your job.

Here’s the honest answer: it’s coming for part of it. The part that, frankly, was never the best use of your time anyway.

Two years ago, a revenue analysis for a mid size attraction might have taken a finance manager the better part of a week, if there was even time at all to do it justice. Pulling data from three systems, cleaning it, building a model, cross referencing against last year, writing up findings. Today, conversational AI can do that same analysis in minutes – deeper, across more variables, industry benchmarks baked in. That’s not a prediction. That’s a Tuesday.

And when analysis goes from days to minutes, something fundamental shifts. The scarce resource is no longer the insight. It’s what you do with it that counts. The bottleneck used to be: Can we get the data? Can we make sense of it? Now it’s: Do we have the judgment to act on what it’s telling us? That changes everything about where human value lives.

What we got wrong (sort of)

Here’s where we owe you something close to a confession.

At Dexibit, we’ve spent years advocating for going from “gut feel to insight inspired”, using data to inform (not drive!) decisions. And we stand by that. Flying blind on instinct alone was never a strategy, it was a coping mechanism for not having the right tools.

But here’s the twist we didn’t fully anticipate at the time: in a world where AI delivers instant insight, your gut is the most valuable thing you’ve got. That’s not a contradiction, but a completion of the loop. In the old world, gut feel was all you had, because analysis was slow, expensive and shallow. Our pitch was simple: stop guessing, start knowing.

In the new world, the knowing is handled. What’s left, what only you can bring, is the judgment, the taste, the experience and the conviction to turn insight into the right action for your institution, your guests and your community. The flip is that insight is now abundant and judgment is what’s scarce.

What “gut” actually means

Let’s be precise about this, because “trust your gut” can sound like permission to ignore evidence and that’s not what we’re saying. What we’re saying is that the human contribution has shifted upstream and it’s worth understanding exactly what that contribution is.

• Pattern recognition from lived experience. You’ve seen how things play out. Not in a dataset, but in a board meeting that went sideways, on a gallery floor during a sold out opening, in the aftermath of a pricing experiment that alienated your community. That memory isn’t anecdotal, it’s intelligence that doesn’t fit in a spreadsheet.
• Contextual awareness no system can hold. The donor whose emails have gotten shorter. The neighboring development that’s about to change your traffic patterns. The staff member who’s burning out but hasn’t said anything yet. This is knowledge that lives in relationships, hallway conversations and the feeling you get walking your venue on a quiet Tuesday morning. It’s the eyebrow that goes up watching the lost opportunity with tourists in your free admission attraction line up expecting to pay and being waved through. Signals that never generate data. 
• Taste. Substance. Style. Not what’s optimal, but what’s right. The exhibition concept that data would never suggest but your community needs. The brand voice that sounds like you, the permission to be playful, not like everyone else. The instinct that a campaign performs but doesn’t resonate. Taste is what separates an institution with a personality from one that’s merely efficient.
• Direction. AI is extraordinarily good at answering questions. But someone has to decide which questions to ask and, just as importantly, which answers to ignore. Direction isn’t a guardrail. It’s a steering wheel. It’s governance in the truest sense: not what AI shouldn’t decide, but where you’re going and therefore what matters.
• Conviction. Three scenarios. Three different projections. One budget cycle. The data says “it depends.” Someone has to make the call. That someone is you.

None of this is fuzzy thinking. It’s expertise that operates above and beyond what any model can reach. As Harvard Business Review recently argued: “The spread of more powerful tools and larger datasets will likely make the human elements of decision-making more differentiating.” 

The experience you carry

This plays out differently depending on where you are in your career.

1. If you’re a veteran fifteen, twenty, thirty years in this industry, your pattern library just became your most valuable asset. You watched online ticketing go from radical to obvious. You’ve seen attitudes on dynamic pricing evolve from heresy to best practice to nuanced strategy. You remember what happened last time attendance dipped like this and you know the difference between a trend and a blip. AI can analyze this quarter’s performance in seconds. It may not have visibility to what happened at your institution in 2012 when you tried that membership restructure and lost 400 households. That memory is your gut and it’s irreplaceable.
2. If you’re newer to the industry, maybe you came in from hospitality, tech or retail during the post pandemic talent reshuffle, your cross sector instincts are a genuine asset. You see patterns that lifers miss. And here’s the good news: AI actually accelerates your path to deep industry knowledge. You can interrogate years of historical data in minutes, pressure test hunches against global benchmarks and close the experience gap faster than any previous generation of professionals could. For you, AI isn’t replacing intuition. It’s building it.

You need each other. And both profiles become dramatically more valuable when paired with the right tools.

The context you hold

Here’s where this gets personal for us. We’ve built Dexibit’s AI to carry an unusual amount of context. It knows your data definitions. It holds strategic notes about your institutional priorities. It understands your operational calendar, like what exhibitions are running, what events are planned, what holidays are coming. It’s tuned to patterns across hundreds of attractions globally. It can listen to the voice of thousands of your visitors and surface what they’re actually saying, in their own words.

That context is what makes Dexibit’s AI analysis in Ask epic, rather than generic. It’s the difference between “your revenue is down 8%” and “your revenue is down 8%, which tracks with the seasonal pattern you flagged given the east wing renovation closing weekends through March and corresponding visitor patterns and feedback.”

But here’s what we’ll always be honest about: you hold more context than any AI ever will. You know the politics. You know the personalities. You know that the community meeting next month could reshape how you position your capital campaign. You know your CFO needs to see the story framed a specific way or it won’t land with them. You know your team is exhausted and that the “optimal” answer isn’t the right one this week.

And here’s the part that makes this a partnership, not a replacement: you’re the one who decides what context Dexibit’s AI in Ask needs. Every time you set a strategic priority, define a term your institution uses differently than the rest of the world, or note why this quarter was unusual, you’re making the analysis smarter for next time. It’s a loop, one which the human (that’s you) keeps tightening.

Where this gets real

• Visitor services. AI can predict crowd surges, optimize staffing models and flag anomalies in wait times before they become complaints. But the human is the one who reads the exhaustion on a father’s face, makes an exception that isn’t in any playbook and turns what could have been a one star review into a story that family tells for years. Those moments of surprise and delight that go way beyond the patterned response and can’t be scripted by an algorithm. They require empathy, authority and the willingness to break a rule because the moment demands it – one of the hallmarks of the experience industry.
• Experience design. AI can analyze dwell times, sentiment and engagement patterns across thousands of exhibitions and environments worldwide. But knowing that this community needs this story, told this way, at this moment in the cultural conversation – that’s taste, creative instinct. It’s true whether you’re curating a gallery show, designing a ride queue narrative, or programming a members’ night.
• Finance. AI can model revenue scenarios, surface risks early and forecast with startling precision. But when three projections tell three different stories and the board meets Friday, someone has to exercise judgment under ambiguity. That’s not a data problem, it’s a leadership one.
• Marketing. This is where the interplay gets fascinating. AI, especially when in Dexibit’s Ask, it can listen to what visitors are actually saying in their own words, gives marketers something they’ve never had at scale: authenticity. Real language. Real emotion. Real patterns of delight and disappointment. But the marketer is the one who decides what story to tell with it. Where to take the brand. When to zig while competitors zag. You can give an AI your brand voice. But someone had to have the taste to define that voice in the first place.

If the value has shifted from analysis to judgment, the skills that make you effective shift too. Not replacing what you already know, adding a layer.

Learn to prompt well. This sounds basic, but it’s the new literacy. The difference between a vague question and a precise one is the difference between generic output and genuine insight. It’s amplified in Ask, the difference between “how many visitors did we get last week” to analyzing what went well versus not, how it compares historically or recently, the context of what was on and how to change the trajectory. Framing the right question: what to include, what to constrain, what to follow up on, is a skill that compounds every time you use it.

Validate, don’t just accept. AI can be wrong. Sometimes confidently. The ability to look at an output and say “that doesn’t match what I know about our visitors” – that’s exactly the gut check that keeps analysis honest. Your experience is the quality control layer.

Understand where your data comes from. You don’t need to be a data engineer. But knowing which systems feed your analytics, what’s clean and what’s messy, where the gaps live, that’s the difference between trusting your tools and trusting them blindly.

Capture context deliberately. This is the one nobody talks about and yet it might be the most important. The AI gets smarter when you feed it what you know. Document your strategic priorities. Note why this quarter was unusual. Define the terms your institution uses differently than the rest of the industry. Think of it as investing in a conversation partner that has a perfect memory, but only for what you’ve shared.

Here’s the uncomfortable truth buried under all the headlines: AI doesn’t threaten the people who use it – instead, it’s the tension between teams who use it deliberately and those who don’t. The Citrini doomsday scenario (mass displacement, economic spiral) may or may not come to pass. But the individual version of that story is already playing out, quietly, every day. The team still spending four days on analysis their counterpart across town finishes before lunch. The director who won’t engage with new tools and can’t understand why the board is asking sharper questions. The marketer writing copy in a vacuum while a competitor is listening to ten thousand visitor voices.

This isn’t about personal obsolescence. It’s about organizational agility. The teams that pair human judgment with AI powered insight will move faster, see further and make better calls… not because the machine replaced the human, but because it freed them to do what they were always best at.

The nature of work is changing. The professionals who thrive, whether they’ve been in this industry for thirty years or three, will be the ones who understand that AI didn’t make them less relevant, it made their humanity the main event. This is your pattern recognition. Your contextual awareness, your taste. Your courage to make the call.

We spent a decade building tools to move this industry from gut feel to insight. Turns out, the future isn’t a single tool: it’s an ecosystem of platforms, data, context and human leadership, all working in concert. We were building something better: a future that finally makes your gut count for everything it’s worth. Trust it.