Why Theme Parks Need AI in the Design Room — Not Just the Marketing Department

By Glara Han | May 2026

When people talk about AI in the theme park industry, the conversation almost always lands in the same place: personalized marketing, dynamic pricing, chatbots for guest services, maybe predictive maintenance. All useful. All real. But all happening after the attraction is already built.

That's the wrong end of the problem.

The most expensive, most painful, most time-consuming challenges in this industry don't happen at the gift shop or the ticketing app. They happen in the design room — years before a single shovel hits the ground. And that's exactly where AI is most needed, and most absent.

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The Problem Nobody Talks About Publicly

After 25 years in this industry, I've seen the same pattern repeat itself on project after project, across continents and budget scales.

A creative team develops a stunning concept. Concept art is produced. The client get excited. The renders are beautiful. And then — months into development — engineering comes back and says the structure can't support the load. Or operations flags that the dispatch cycle makes the capacity target impossible. Or the safety envelope requires a redesign of the signature element that everyone fell in love with.

By that point, the team has already spent months and significant capital on a direction that doesn't work.

The problem isn't creativity. This industry has no shortage of imagination. The problem is that Creative, Engineering, Operations, Capacity Planning, and Safety all operate in sequence — one after the other — instead of simultaneously. By the time the people who understand operational reality get to weigh in, the creative direction is already locked in emotionally, if not contractually.

Every redesign cycle is capital destroyed before the first shovel hits the ground.

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What AI Actually Changes

The most powerful thing AI can do in attraction development isn't generate images. It's eliminate the sequential review problem.

Imagine a development process where, as a creative concept takes shape, the system is simultaneously running capacity simulations, flagging structural constraints, modeling dispatch intervals, and projecting investor-relevant feasibility metrics — in real time, as decisions are being made. Not weeks later in a review meeting. Not after the concept art budget is spent.

That's what I'm building.

The system doesn't replace the creative team. It doesn't replace the engineers or the operations experts. What it does is give every discipline a voice at the table from day one, so that the concept that gets developed is one that can actually be built, operated, and scaled.

For investors, this changes everything. The first fundable question for any experiential entertainment project isn't "Is it beautiful?" It's "Can it be built, operated, and scaled profitably?" An AI-integrated development pipeline answers that question early — before the expensive commitments are made.

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A Real Example: What a Phase 1 Review Actually Reveals

Earlier this year, I ran a Phase 1 concept review on xxxxx xxxx — a synchronized multi-lane racing attraction concept that I've been developing. It's a hybrid system: part coaster, part competitive racing experience, with engineered competition logic that creates the illusion of real racing while maintaining full operator control over safety and throughput.

Running a proper Phase 1 review — even at a concept level — requires thinking simultaneously across at least six dimensions: ride system mechanics, structural engineering assumptions, banking and speed parameters, capacity and dispatch modeling, safety systems, and experience framework. Miss any one of them early, and you're building on a foundation that will fail later.

Here's what the analysis surfaced immediately:

Speed vs. Scale is a non-negotiable trade-off. Higher racing speeds require larger turn radius to manage lateral G-forces. As speed increases, the attraction footprint expands — longer curves, wider clearance zones, extended braking sections. If your site has footprint constraints, your speed targets have to adjust from day one, not after your track layout is drawn.

Capacity is killed by complexity. A 3-lane system creates spectacle and competitive energy. It also introduces exponentially more operational complexity: more restraint verification points, more synchronization logic, higher probability of one lane delaying the full dispatch cycle. In a traditional development process, the operations team would flag this after the creative direction is set. An AI-integrated system surfaces it while the lane count is still a variable.

The competitive feel requires engineering, not physics. True free-roam racing — where outcomes are determined by driver skill — introduces unacceptable variability in safety, timing, and guest experience consistency. The solution is what I call Engineered Competition Logic: the system delivers the feeling of racing while outcomes are programmed, not physics-based. This is the core design insight, and it has significant implications for the control architecture, vehicle design, and safety systems — all of which need to be developed in parallel, not in sequence.

These are the kinds of insights that, in a traditional workflow, might not emerge until the engineering review phase — months into development. In an AI-assisted pipeline, they're part of the initial concept framework.

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What This Means for the Industry

The theme park and experiential entertainment industry is at an inflection point. Guest expectations are higher than ever. IP competition is intensifying. Construction costs and timelines are not going down. In that environment, the developers who win will be the ones who can move from vision to buildable, operable reality faster and with fewer costly pivots.

AI in the marketing department is a nice optimization. AI in the design room is a structural advantage.

I spent 25 years learning how these systems work from the inside — from master planning and attraction design to on-site installation and operations, across projects in the US, Korea, and across Asia. I've held three US patents on ride systems. And now I'm applying everything I know to build the development pipeline this industry has needed for a long time.

The goal isn't to automate creativity. It's to give creativity the operational foundation it needs to actually reach guests.

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A Final Thought

The next major attraction that opens at a major theme park — the one that becomes a signature, a destination, a reason to buy a ticket — was designed years ago, in a room where creative people were trying to solve hard operational problems simultaneously.

AI doesn't change what those people are trying to do. It changes how fast they can find out if they're building something real.

That's the design room AI that this industry needs.

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Glara Han is a theme park designer and attraction developer with 25 years of experience and three US patents in ride systems. She is currently developing an AI-integrated attraction development pipeline for theme parks, LBE, and experiential entertainment. To connect or collaborate: glarah.com/contact